shamsun nahar msc (accounting and finance), uk m.b.a, b.b

Risk Disclosure Practices: Their Determinants and Association with Bank

Performance

Shamsun Nahar MSc (Accounting and Finance), UK

M.B.A, B.B.A (Accounting and Information system), Bangladesh

A Thesis Submitted in Fulfilment of the Requirements for the Degree of

Doctor of Philosophy

Faculty of Business and Enterprise

Swinburne University of Technology

2015

Abstract

In recent times, corporate risk disclosure has been an issue of major concern to the

global community and has gained considerable attention from stakeholders, policy

makers and regulators. This research explores risk disclosures practices, their

determinants and association with bank performance in the context of a developing

country, Bangladesh. Most existing studies on risk disclosure provide empirical

evidence from developed countries. However, the difference in institutional and socio-

economic settings between developed and developing countries might affect the extent

of corporate risk disclosure differentially. Specifically, Bangladesh makes an ideal site

in which to examine risk disclosures and their determinants within an agency and neo

institutional isomorphism conceptual framework because risk disclosures are effectively

voluntary.

This research is comprised of three interrelated Phases. Employing content analysis, the

first Phase investigates corporate risk disclosure practices by sample banks from 2006

to 2012. A comprehensive Risk Disclosure Index (RDI) is developed based on

international standards and is used as a benchmark against which to score actual risk

disclosures. The second Phase investigates determinants for such disclosures. Informed

by thematic analysis of semi-structured interviews with senior banking executives and

regulators, this Phase investigates the Risk Disclosure Index score and its association

with banks’ corporate governance and financial characteristics. The third and final

Phase uses multiple regression analysis to investigate the association between the extent

of risk disclosure and performance. Bank performance is measured using two broad

aspects: bank operating performance and bank valuation.

Overall, the Risk Disclosure Index developed in this study is of relevance to financial

institutions seeking to provide information for stakeholders and, indeed, to all relevant

parties seeking to assess or evaluate information in relation to risk disclosure. The

analysis suggests that listed banks in Bangladesh made significant improvement in risk

disclosure over time, predominantly on a voluntary basis, and this improvement is

associated with several key bank characteristics, consistent with agency and neo

ii

institutional isomorphism tenets. In addition, analysis of interview findings suggest that

institutional weakness, political interference and inadequate monitoring by the Central

Bank hinders risk disclosure practices. The findings provide evidence also that lagged

risk disclosure is positively associated with banks’ return on assets, solvency and

employee efficiency. This research should assist also accounting regulators and

legislators in developing reporting requirements that satisfy stakeholders’ demands in

relation to risk disclosure. Research implications from the findings are discussed,

together with limitations and recommendations for future research.

iii

Acknowledgement

First, I am grateful to almighty Allah for granting me strength and courage to the long,

arduous journey towards the completion of the PhD thesis.

Writing this thesis is not like making a journey alone. I would like to express my

gratitude and acknowledgement to many people for their guidance and support along

my PhD journey.

My deepest gratefulness for support and encouragement throughout my doctoral study

goes to my supervisor, Dr. Mohammad Azim. He had always been kind to me,

providing me advice and guidance throughout my entire journey. I owe him a big

gratitude.

This project could not be completed without the input and guidance provided by

Professor Christine Jubb. Her extremely valuable feedback and timely suggestions are

much appreciated. It has been my privilege to have her as my supervisor. Thank you.

I am also thankful to Dr Ron Kluvers, for all his beneficial advice and guidance. I am

sincerely pleased to the interview participants, who shared their time, knowledge and

wisdom with me and everyone who has taken part in this study. I appreciate my

distinguished colleagues in the PhD research lab at Swinburne University for their

support and friendship.

My efforts and dreams would not be materialised if Swinburne University of

Technology would not have provided me prestigious Swinburne University

Postgraduate Research Award (SUPRA) for doing PhD.

I would like to acknowledge my family- my husband, brothers, sisters, brother- in-law

and my dearest parents for having faith in my capabilities, giving me unconditional

iv

support and continuous encouragement. Very special thanks to my three-year-old ‘little

superman’ son, Rayyan, my biggest source of inspiration throughout this long journey.

Thank you.

Lastly, I wish to convey my gratitude to all my friends who always provided valuable

support, interest, and help in every possible way throughout the process of this study.

v

Declaration

This thesis contains no material that has been accepted for the award of any other

degree or diploma in any other institution. To the best of my knowledge, the work of no

other person has been used without due acknowledgement, and the thesis is not written

in collaboration with any other person.

Shamsun Nahar

June, 2015

vii

Table of contents

Abstract…………. ............................................................................................................ i

Acknowledgment ............................................................................................................ iii

Declaration ....................................................................................................................... v

Table of Contents .......................................................................................................... vii

List of Tables ................................................................................................................. xv

List of Figures .............................................................................................................. xvii

List of Appendices ........................................................................................................ xix

PART ONE 1 PRELIMINARIES 1

Chapter 1: Introduction 1

1.1 Introduction ................................................................................................................. 3

1.2 Research background and motivation ......................................................................... 4

1.3 Research justification and objectives .......................................................................... 7

1.4 Key terms .................................................................................................................... 9

1.5 Research approach .................................................................................................... 10

1.6 Research contribution…………………………………………………………… 12

1.7 Thesis outline……………………………………………………………………… 12

Chapter 2: Risk Reporting as an Issue of Concern 14

2.1 Introduction ............................................................................................................... 15

2.2 Background to risk reporting .................................................................................... 15

2.2.1 Changes in business environment and emergence of risk reporting ................. 16

2.2.2 Risk reporting as an issue of concern in banking institutions .......................... 18

2.3 Risk disclosure related policies, pressures and corporate responses......................... 19

2.4 Institutional arrangements and accounting regulations ............................................. 21

2.4.1 Cadbury Report ................................................................................................ 21

2.4.2 The American Institute of Certified Public Accountants .................................. 22

2.4.3 The Institute of Chartered Accountants in England and Wales ........................ 22

2.4.4 Hampel Report ................................................................................................. 24

2.4.5 Higgs Report and Smith Report ....................................................................... 24

2.4.6 International Financial Reporting Standards .................................................... 24

2.4.7 BASEL II: Pillar 3 (Market Discipline) ............................................................ 26

2.5 Risk disclosure as a major concern in Bangladesh ................................................... 28

viii

2.6 Chapter conclusion .................................................................................................... 31

Chapter 3: Bangladesh- the Context of the Study 33

3.1 Introduction ............................................................................................................... 33

3.2 Bangladesh as the country of study ........................................................................... 33

3.2.1 Bangladesh: Country profile ............................................................................. 34

3.2.2 Political and historical context .......................................................................... 34

3.2.3 Economic context .............................................................................................. 35

3.2.4 Socio-cultural context ........................................................................................ 38

3.2.5 Legal and institutional context .......................................................................... 39

3.3 The financial system in Bangladesh .......................................................................... 43

3.4 Banking industry in Bangladesh ............................................................................... 44

3.4.1 Evolution of banking industry ........................................................................... 45

3.4.2 Structure of the banking sector in Bangladesh .................................................. 45

3.5 Financial reforms in banking sector .......................................................................... 47

3.5.1 Risk measure policy reforms in banks .............................................................. 49

3.5.2 Institutional reform of risk measures ................................................................. 51

3.5.3 Legal reform ...................................................................................................... 53

3.6 Motivation for choosing Bangladesh as the context for this study ........................... 53

3.7 Motivation for selecting listed banks in Bangladesh ................................................ 55


PART TWO 59

LITERATURE REVIEW AND THEORETICAL UNDERPINNING 59

Chapter 4: Literature Review 61

4.1 Introduction ............................................................................................................... 61

4.2 Risk and risk disclosure ............................................................................................ 62

4.2.1 The concept of risk ............................................................................................ 62

4.2.2 Classification of risk .......................................................................................... 63

4.3 The concept of disclosure in accounting and economics research ............................ 65

4.4 Risk disclosure: Review of previous studies ............................................................. 66

4.4.1 Empirical studies of risk reporting by banking institutions .............................. 69

4.4.2 Empirical studies of risk reporting in other than banking institutions .............. 71

4.5 Gaps in the literature ................................................................................................. 86


ix

Chapter 5: Conceptual Framework and Hypotheses 89

5.1 Introduction ............................................................................................................... 89

5.2 Theories discussed in previous disclosure studies .................................................... 90

5.3 Agency theory ........................................................................................................... 90

5.3.1 The agency problem .......................................................................................... 91

5.3.2 Agency theory and the organisational perspective ............................................ 93

5.3.3 Relevance of agency theory in this study: Development of Hypotheses .......... 95

5.4 Institutional theory .................................................................................................... 97

5.4.1Defining institution ............................................................................................. 98

5.4.2 New institutionalism ........................................................................................ 101

5.4.3 Significance of institutional isomorphism ....................................................... 102

5.4.4 Isomorphism processes .................................................................................... 103

5.4.4.1 Coercive isomorphism ............................................................................. 103 5.4.4.2 Mimetic isomorphism .............................................................................. 105 5.4.4.3 Normative isomorphism .......................................................................... 107

5.5 The relation between risk disclosure and bank performance .................................. 108

5.5.1 Employee efficiency ........................................................................................ 109

5.5.2 Solvency efficiency ......................................................................................... 109

5.5.3 Deposit concentration ...................................................................................... 111

5.5.4 Financial performance ..................................................................................... 111

5.5.5 Risk disclosure and bank valuation ................................................................. 112

5.6 Conceptual framework ............................................................................................ 112

5.7 Chapter conclusion .................................................................................................. 113

PART THREE 116

METHODOLOGY ............................................. 116

Chapter 6: Research Methodology 118

6.1 Introduction ............................................................................................................. 118

6.2 Philosophical assumption ........................................................................................ 119

6.2.1 Ontological assumption ................................................................................... 120

6.2.2 Epistemological assumption ............................................................................ 121

6.3 Research type .......................................................................................................... 122

6.4 Theoretical perspective ........................................................................................... 122

6.5 Methodology ........................................................................................................... 123

6.5.1 Quantitative research approach ....................................................................... 123

6.5.2 Qualitative research approach ......................................................................... 124

x

6.5.3 Mixed method approach .................................................................................. 124

6.5.4 Paradigm adopted in this study ....................................................................... 125

6.5.5 Designing triangulation in mixed method research ......................................... 125

6.5.6 The convergence model of triangulation ......................................................... 127

6.6 The quantitative method .......................................................................................... 129

6.6.1 Research instrument ........................................................................................ 129

6.6.1.1 Content analysis approach ....................................................................... 129 6.6.1.2 Risk Disclosure Index .............................................................................. 131

6.6.2 Reliability of Risk Disclosure Index score ...................................................... 153

6.6.3 Sample design .................................................................................................. 154

6.6.4 Data collection ................................................................................................. 154

6.6.5 The dependent variable ................................................................................... 154

6.6.6 Independent and control variables ................................................................... 155

6.6.7 Statistical data analysis techniques .................................................................. 155

6.6.7.1 Descriptive statistics ................................................................................ 156 6.6.7.2 Univariate statistics .................................................................................. 156 6.6.7.3 Bivariate analysis .................................................................................... 157 6.6.7.4 Multiple regression model ....................................................................... 157

6.6.8 Sensitivity and supplemental analysis ............................................................. 166

6.7 The qualitative method ............................................................................................ 167

6.7.1 Justification of sampling procedure ................................................................ 168

6.7.2 Designing interview protocol .......................................................................... 169

6.7.3 Designing the interview protocol .................................................................... 169

6.7.4 Data collection technique ................................................................................ 170

6.7.5 Data analysis .................................................................................................... 171

6.7.6 Reliability and validity .................................................................................... 172

6.8. Ethical clearance .................................................................................................... 173


PART FOUR 174 ANALYSIS .......................................................... 174

Phase One

Chapter 7: Content Analysis of Annual Reports………………………….. 170

7.1 Introduction ............................................................................................................. 176

7.2 Trends in total corporate risk disclosure ................................................................. 177

7.2.1 Risk disclosure by key categories ................................................................... 193

7.2.2 Risk disclosure by Risk Types ........................................................................ 194

xi

7.2.3 Qualitative and quantitative disclosure ........................................................... 195

7.3 Descriptive statistics for the Risk Disclosure Index ............................................... 196

7.4 Comparison of Risk Disclosure Index over the period: Univariate analysis ......... 199

7.4.1 Significance of Risk Disclosure Index over the period: ANOVA .................. 199

7.4.2 Conventional and non-conventional banks .................................................... 200

7.4.3 Comparisons of pre- and post GFC periods .................................................... 201

7.5 Discussion of results ............................................................................................... 203


Phase Two

Chapter 8: Qualitative Analysis of Interview Data 206

8.1 Introduction ............................................................................................................. 206

8.2 Risk disclosure practices and rationale for disclosure ............................................ 208

8.3 Determinants of risk disclosure ............................................................................... 210

8.3.1 Institutional isomorphism ................................................................................ 211

8.3.2 Risk governance factors .................................................................................. 214

8.4 Additional findings from interviewees.................................................................... 216

8.4.1 Institutional weakness ..................................................................................... 216

8.4.2 Political interference ........................................................................................ 218

8.4.3 Lack of central bank autonomy ....................................................................... 220

8.4.4 Lack of accountability ..................................................................................... 221

8.4.5 Lack of demand from governments ................................................................. 221

8.4.6 Lack of education ............................................................................................ 222

8.4.7 Brief and concise report .................................................................................. 223


Chapter 9: Descriptive, Univariate and Bivariate Analyses 226

9.1 Introduction ............................................................................................................. 226

9.2 Sample and source of data ...................................................................................... 227

9.3 Descriptive statistics................................................................................................ 227

9.4 Univariate statistics: ANOVA and Chi-Square tests .............................................. 238

9.4.1 Significance of mean over time: ANOVA ...................................................... 238

9.4.2 Continuous variable: T tests ............................................................................ 238

9.4.3 Categorical variables: Chi-Square tests ........................................................... 239

xii

9.5 Bivariate analysis .................................................................................................... 240


Chapter 10: Factors Underlying Risk Disclosure: Multivariate Statistics 246

10.1 Introduction ........................................................................................................... 246

10.2 Multivariate regression model .............................................................................. 247

10.3 Normality and multicollinearity ............................................................................ 248

10.3.1 Normality ....................................................................................................... 248

10.3.2 Multicollinearity ............................................................................................ 251

10.4 Multiple regression results: Hypothesis testing .................................................... 253

10.4.1 Agency theory and Risk Disclosure Index ................................................... 255

10.4.2 Institutional isomorphism and Risk Disclosure Index .................................. 256

10.4.3 Control variables ........................................................................................... 257

10.5 Sensitivity analysis ................................................................................................ 257

10.6 Robustness check .................................................................................................. 261

10.6.1 Association of Risk Disclosure Index with profitability ............................... 261

10.6.2 Five types of Risk Disclosure ........................................................................ 263

10.7 Change in Risk Disclosure Index across the sample periods ................................ 268

10.8 Discussion of results ............................................................................................. 276

10.9 Chapter conclusion ................................................................................................ 278

Phase Three

Chapter 11: Risk Disclosure and Bank Performance 279

11.1 Introduction ........................................................................................................... 279

11.2 Descriptives, t-tests and correlations..................................................................... 283

11.3 Regression analysis ............................................................................................... 287

11.4 Supplemental analysis ........................................................................................... 291

11.4.1 Bank performance in risk disclosure groups ................................................. 291

11.4.2 Bank performance and risk disclosure in Non-Islamic and Islamic banks ... 297

11.4.3 Bank performance and Risk Types ............................................................... 300

11.5 Discussion of results ............................................................................................. 312

11.6 Chapter conclusion ................................................................................................ 313

xiii

PART FIVE 314 CONCLUSION ......................................................... 314

Chapter 12: Conclusion 316

12.1 Introduction ........................................................................................................... 316

12.2 Overview ............................................................................................................... 317

12.3 Research findings and implications ...................................................................... 322

12.4 Research contribution............................................................................................ 325

12.5 Research limitations .............................................................................................. 328

12.6 Suggestions for future research ............................................................................. 329

References .......................................................................................................... 333

Appendices ......................................................................................................... 351

xv

List of Tables

Table 1.1: Key terms ......................................................................................................... 9

Table 3.1: Economy of Bangladesh ................................................................................ 37

Table 3.2: Structure of the banking system in Bangladesh ............................................. 46

Table 3.3: Bank branches in urban and rural areas (up to June 2013) ............................ 47

Table 4.1: Classification of risk in extant literature ........................................................ 64

Table 4.2: Empirical studies of corporate risk disclosure ............................................... 77

Table 5.1: Components of institutional analysis ........................................................... 100

Table 5.2: The new and old institutionalism ................................................................. 101

Table 6.1: Paradigmatic concerns and research approaches ......................................... 125

Table 6.2: Risk Disclosure Index .................................................................................. 134

Table 6.3: Reliability tests of Risk Disclosure Index comparability ............................ 153

Table 6.4: Variable definitions (Model 1)..................................................................... 161

Table 6.5: Variable definitions (Models 2-7) ................................................................ 165

Table 6.6: Variable definition ....................................................................................... 167

Table 7.1: Average Risk Disclosure Index (RDI) score .............................................. 178

Table 7.2: Mean Risk Disclosure Index score (per cent of max. possible [147]) ......... 179

Table 7.3: Mean Risk Disclosure Index (RDI) score (%) by category ......................... 193

Table 7.4: Mean Risk Disclosure Index (RDI) score (%) by Risk Type .................... 194

Table 7.5: Mean Qualitative and Quantitative Risk Disclosure Index (RDI) score ...... 196

Table 7.6: Descriptive statistics for seven key categories of Risk Disclosure Index .... 197

Table 7.7: Descriptive statistics for seven categories individually and aggregately ..... 198

Table 7.8: Risk Disclosure Index (%) by year ANOVA ............................................... 199

Table 7.9: Mean difference between conventional and non-conventional ................... 200

Table 7.10: Wilcoxon Signed Rank tests ...................................................................... 201

Table 7.11: Paired sample t tests of mean RDI (%) across discrete periods ................. 202

Table 7.12: Paired sample t-tests .................................................................................. 203

Table 9.1: Descriptive statistics by complete sample ................................................... 229

Table 9.2(Panel A): Descriptive statistics year 2006 .................................................... 231

Table 9.2(Panel B): Descriptive statistics year 2007 .................................................... 232

Table 9.2(Panel C): Descriptive statistics year 2008 .................................................... 233

Table 9.2(Panel D): Descriptive statistics year 2009 .................................................... 234

Table 9.2(Panel E): Descriptive statistics year 2010 .................................................... 235

Table 9.2(Panel F): Descriptive statistics year 2011 ..................................................... 236

xvi

Table 9.2:(Panel G): Descriptive statistics year 2012 ................................................... 237

Table 9.3: ANOVA by year .......................................................................................... 238

Table 9.4: t tests for continuous variables ................................................................... 238

Table 9.5: Pearson Chi-Square test for categorical variables ....................................... 240

Table 9.6: Pearson’s Correlations Pooled Data............................................................. 242

Table 10.1: Variable Definitions ................................................................................... 248

Table 10.2: Normality analysis for pooled data ............................................................ 250

Table 10.3: Collinearity statistics for pooled data ........................................................ 252

Table 10.4: Pooled OLS robust regression results for Risk Disclosure Index .............. 254

Table 10.5: Pooled OLS regression results for the Risk Disclosure Index ................... 259

Table 10.6: Pooled OLS regression results for Risk Disclosure Index ......................... 260

Table 10.7: Pooled OLS regression results for Risk Disclosure Index ......................... 262

Table 10.8: Pooled OLS regression results for five types of risks ................................ 265

Table 10.9: Variable definitions .................................................................................... 269

Table 10.10:Change in Risk Disclosure Index in pre and post GFC periods ............... 272

Table 10.11: Summary of significant variables from Table 10.10 ............................... 274

Table 10.12: Difference in Mean Risk Disclosure between the periods ....................... 275

Table 11.1: Variable definitions .................................................................................... 282

Table 11.2: Descriptive and t- statistics by complete sample ....................................... 284

Table 11.3: Pearson’s Correlations Pooled Data........................................................... 286

Table 11.4: Regression model (Models 2-7) ................................................................. 289

Table 11.5: Descriptive Statistics and t-tests for variables ........................................... 293

Table 11.6: Regression results for High and Low Risk Disclosure groups .................. 295

Table 11.7: Regression results for High and Low Risk Disclosure groups .................. 298

Table 11.8: Regression results -Lag_Market Risk Disclosure Index ............................ 302

Table 11.9: Regression results -Lag Credit Risk Disclosure Index .............................. 304

Table 11.10: Regression results -Lag Solvency Risk Disclosure Index ....................... 306

Table 11.11: Regression results -Lag Operational Risk Disclosure Index ................... 308

Table 11.12: Regression results -Lag Equities Risk Disclosure Index ......................... 310

Table 12.1: This thesis’ research at a glance................................................................. 318

xvii

List of Figures

Figure 1.1: Roadmap of Chapter ....................................................................................... 3

Figure 1.2: Depiction of the framework for this research ................................................. 9

Figure 1.3: Research purpose and the three Phases ........................................................ 11

Figure 1.4: Structure of the thesis ................................................................................... 13

Figure 2.1: Roadmap of Chapter ..................................................................................... 15

Figure 2.2: Factors affecting financial reporting............................................................. 17


Figure 3.2: The national flag and map of Bangladesh .................................................... 35

Figure 3.3: Structure of the financial system in Bangladesh .......................................... 44

Figure 3.4: Bangladesh real GDP growth ....................................................................... 55

Figure 3.5: Deposits in years 2008-2012 ........................................................................ 56

Figure 3.6: Deposits in the banking sector, 2012 ............................................................ 56

Figure 3.7: Percentage share of assets (2007-2012)........................................................ 57



Figure 5.2: Agency theoretical perspective ..................................................................... 93

Figure 5.3: Conceptual framework for this study ......................................................... 113

Figure 6.1: Roadmap of Chapter ................................................................................... 118

Figure 6.2: Continuum of ontological assumptions ...................................................... 120

Figure 6.3: The convergence model used in this study ................................................. 127

Figure 6.4: Summary of the research design ................................................................. 128

Figure 6.5: Narratives in annual reports ........................................................................ 130

Figure 6.6: Qualitative data analysis technique ............................................................ 172

Figure 7.1: Roadmap of Chapter 7 ................................................................................ 177



Figure 10.1: Roadmap of Chapter 10 ............................................................................ 247

Figure 11.1: Roadmap of Chapter 11………………………………………………… 282

xix

List of Appendices

Appendix 6.1: Research paradigmatic dichotomies………………………………. 349

Appendix 6.2: Research types……………………………………………………… 350

Appendix 6.3: Summarises the prototypical characteristics of mixed method…… 351

Appendix 6.4: Interview Protocol ………………………………………………… 352

Appendix 6.5: Consent form………………………………………………………… 354

Appendix 6.6: Ethics Approval Letter………………………………………………. 356

Appendix 7.1: Tukey HSD………………………………………………………… 359

Appendix 7.2: Eta squared statistic ……………………………………………….. 360

Appendix 9.1: Presents the post hoc Tukey p values in each year………………… 361

Appendix 9.2: Eta squared statistic………………………………………………….. 364

Appendix 10.1: Correlations A-E……………………………………………………. 365

Appendix 10.2: Correlations change Risk Disclosure Index 2006 and 2008………... 370

Appendix 10.3: Correlations change Risk Disclosure Index 2006 and 2012 …….. 371

Appendix 10.4: Correlations change Risk Disclosure Index 2006 and 2010……... 372

Appendix 10.5: Correlations change Risk Disclosure Index 2010 and 2012……... 373

1

PART ONE

PRELIMINARIES

Part one of this thesis introduces the research background and provides the structure of

the thesis. Chapter 1 presents an overview of the study. It starts with a brief discussion

of the background to the research, objectives of the study, research approach and

outlines the structure of the thesis. Chapter 2 provides discussion of the issue of risk

reporting in detail and Chapter 3 provides an overview of Bangladesh as a country and

why it is chosen as the location for this study.

Chapter 1: Introduction

Chapter 2: Risk reporting as an issue of concern

Chapter 3: Bangladesh – the context of the study

3

CHAPTER 1: Introduction

1.1 Introduction

This study extends our knowledge by undertaking an empirical investigation into

financial institutions’ corporate risk disclosure practices in an effectively voluntary

environment, the determinants of those practices and their association with financial

performance. This is an underexplored area in receipt of little attention in the financial

reporting literature.

Briefly, the study consists of three interrelated Phases under a common theme of ‘risk

disclosure practices: their determinants and their association with bank performance’.

The first Phase of the study investigates the corporate risk disclosure practices of all

listed banks in Bangladesh over a seven-year period (2006-2012). The second Phase

investigates the determinants of these corporate risk disclosure practices. The third and

final Phase of the study investigates the association of corporate risk disclosure with

bank performance. Taken together, the three Phases enhance and advance corporate risk

reporting research using various methodological lenses and perspectives. The purpose

of this Chapter is to provide an overview of the study. Figure 1.1 provides a roadmap of

this Chapter.

1Figure 1.1: Roadmap of Chapter

Introduction (1.1) Research

background and

motivation (1.2)

Introduction (1.1)

Glossary of key

terms (1.4)

Research

justification and

objectives (1.3)

Thesis outline

(1.6)

Research approach

(1.5)

4

1.2 Research background and motivation

Corporate risk disclosure has been, and continues to be, a major issue of concern to the

global community and has gained considerable attention from stakeholders (e.g. Aebi,

Sabato & Schmid 2012; Beltratti & Stulz 2012; Erkens, Hung & Matos 2012). From a

business perspective, risk disclosure assists corporations to manage changes and instruct

the path for the future (Abraham & Cox 2007). From a stakeholders’ perspective, ‘risk

profile, risk appetite, and risk management are key elements in making sound

investment decisions’ (Lajili 2009, p.94) and reducing information asymmetry (Botosan

1997; Chang 1998).

Corporate risk disclosure provides information about the company’s material risks that

help stakeholders understand and evaluate the interrelated risks, the effect of risks and

the company’s risk management strategies (Caldwell 2012). Additionally, corporate risk

disclosure lowers the cost of capital as investors achieve greater confidence in the

business operations when uncertainty is reduced (Abraham & Cox 2007; Linsley &

Shrives 2000). Compared with ill-informed investors, the confident and well-informed

investor can assess more accurately the worth of a company’s stock (Deumes &

Knechel 2008) and these (risk) disclosures bring general gains in economic efficiency

(Frolov 2004 ).

Correspondingly, corporate risk disclosure is being recognised increasingly in studies as

a fundamental of business disclosure through provision of transparent information (e.g.

Abraham & Cox 2007; Beretta & Bozzolan 2004; Cabedo & Miguel Tirado 2004;

Hassan 2009; Linsley, Shrives & Crumpton 2006). These studies investigate corporate

risk disclosure given that users of financial reports are demanding relevant risk

information increasingly in order to assess the financial position of a company (Uddin

& Hassan 2011). Moreover, the Global Financial Crisis (GFC) of 2007-2008 raised

significant concern in relation to corporate risk disclosure by banking institutions

(Beltratti & Stulz 2012; Brunnermeier 2009; Conyon, Judge & Useem 2011; Erkens,

Hung & Matos 2012; Fahlenbrach, Prilmeier & Stulz 2011; John & Fred 2009; Milne &

Wood 2008). These authors assert that this period is the worst financial phase after the

Great Depression of the 1930s.

5

Despite the growing attention on and importance of corporate risk disclosure,

considerable bodies of literature that reflect detailed academic work on disclosure and

on corporate governance, there remains limited research on corporate risk disclosure. In

particular, research linking risk disclosure with governance mechanisms, is rare

(Abraham & Cox 2007; Lajili 2009; Lajili & Zéghal 2005). According to Linsley and

Shrives (2005a), although various aspects of disclosure have been investigated in the

last 20-30 years, risk disclosure has not yet been examined seriously.

Most existing studies on risk disclosure, whether in financial or non-financial

institutional settings, provide empirical evidence from developed countries. The extant

studies focus on Anglo-Saxon countries (e.g. Abraham & Cox 2007; Deumes &

Knechel 2008; Lajili 2009; Lajili & Zéghal 2005; Linsley & Lawrence 2007; Linsley,

Shrives & Crumpton 2006; Solomon et al. 2000); European Latin countries (e.g.

Oliveira, Rodrigues & Craig 2011), French (e.g.Thuélin, Henneron & Touron 2006);

Asian countries (e.g. Mohobbot 2005); and Arab countries (e.g. Hassan 2009).

However, the difference in institutional and socio-economic settings might affect the

extent and nature of corporate risk disclosure differentially in between developed and

developing countries. For example, institutional pressure might create doubts about the

effectiveness of the Anglo-Saxon model of corporate governance when applied in

developing countries (Khan, Muttakin & Siddiqui 2013). Developing countries, which

are economically more vulnerable, many have not yet implemented international

disclosure standards from which they might benefit.

The International Accounting Standards Board (IASB) issued International Financial

Reporting Standard (IFRS) 7 (Financial Instruments: Disclosures) in 2005 to become

effective in January 2007. However, the slowdown in the global economy during the

GFC (2007-2008) and the increasing demand for risk reporting highlighted diverse risk

reporting practices, some of which were deficient, resulting in several regulatory

amendments in IFRS 7. In the banking industry, another relevant standard is Basel II:

Market Discipline (hereafter international standards), which was issued by the Basel

Committee on Banking Supervision (BCBS) in 2004. Basel II provides

recommendations on banking laws and regulations, guidelines for accounting practices

6

and disclosure and creates requirements in some countries. The implementation process

of Basel II: Market Discipline was generally slow prior to 2007-2008 until the GFC

caused a major banking crisis through default credit, mortgage backed securities, and

similar derivatives (Barth & Landsman 2010; Brunnermeier 2009). The issuance of

global guidance in relation to risk reporting, and its tightening via amendments over

time in the context of the GFC, offers the opportunity to document corporate responses

and to examine changes in reporting practices over time. Examining these changes in a

developing country is especially important since the changes are likely to be from a

comparatively low base of risk disclosure. Bangladesh, among the developing

countries, marked the beginning of a major development in its financial reporting

through implementing both of these international standards after the GFC (2007-2008).

In addition, the presence of a number of listed banks (30) in Bangladesh provides an

adequate sample for the collection of information and provides sufficient statistical

power for this longitudinal study to provide rigorous results. Moreover, the population

of banks in Bangladesh consists of both conventional (i.e. interest-based operations) and

non-conventional (Islamic Shariah based, i.e. profit/loss sharing mode) banks. The

practice of non-conventional (Islamic) banking in Bangladesh, which follows Islamic

Shariah law, might mean different levels of corporate risk disclosure compared with that

of conventional banks. For these reasons, corporate risk disclosure, particularly in the

banking industry, is deserving of greater research attention than it has received to date.

Previous studies (e.g. Abraham & Cox 2007; Dobler, Lajili & Zéghal 2011; Lajili 2009;

Linsley & Shrives 2005a) investigate corporate risk disclosures and the determinants of

these empirically by examining annual reports, however, very little is known about

regulators’ perceptions of the determinants of corporate risk disclosure. As regulators

are involved, either directly or indirectly, in the risk reporting process, it is important to

explore regulators’ insights in order to achieve a better understanding. This study

reports analysis of interviews with senior regulators and bank officials in order to

provide greater insights to evidence from empirical analysis. Access to such senior

personnel is rare and no prior disclosure studies combine evidence from multiple

sources in the way this study achieves. Briefly put, this research aims to investigate risk

7

disclosure practices, their determinants and the association of risk disclosure with

financial performance by banking institutions in a comprehensive longitudinal study

using Bangladesh as the institutional setting using both quantitative and qualitative

research methods.

1.3 Research justification and objectives

There are three objectives of this study. The first objective is to examine corporate risk

disclosure practices as evidenced in Bangladesh listed banks’ annual reports over a

seven-year period (2006-2012). The purpose of this longitudinal study is to provide a

snapshot of the volume and types of risk disclosure and examine whether the issuance

of international standards (IFRS 7 and Basel II: Market Discipline) triggered changes in

corporate risk disclosure. In addition, the lack of longitudinal studies investigating

changes in risk disclosure behaviours by banks motivates this study, which attempts to

fill a research gap and add to the existing body of knowledge on risk disclosure

practices. It is of interest to investigate how risk reporting has developed over time in

response to the development of new international standards and codes of corporate

governance (Ahsan, Skully & Wickramanayake 2009) in order to evaluate likely future

changes, for example in response to implementation of Basel III1. This is especially so

in a developing country such as Bangladesh due to implementation of Basel III in 2015

(Siddikee, Parvin & Hossain 2013).

The second objective is to identify the relationship between risk disclosure and bank

characteristics. The findings of previous studies (Helbok & Wagner 2006; Hossain

2008) reveal that the extent of risk disclosure is related to bank characteristics, however

perceptions by regulators in relation to risk disclosure determinants has been unexplored

in previous studies. This study focuses on the determinants of risk disclosure by testing

data gathered from annual reports empirically and, in addition, by interviewing

representatives from the banking regulatory sphere to identify their perceptions about

risk disclosure.

1 Basel III was initially scheduled to be implemented from 2013 until 2015; however, the implementation

process is now extended until March 2019.

8

The third objective of this study is to investigate the association of risk disclosure with

banks’ financial performance. Previous studies offer insights into the potential

usefulness and perceived benefits and cost of disclosure (Botosan 1997; Lajili 2009;

Linsley, Shrives & Crumpton 2006). These authors assert that improved disclosure

enhances corporate transparency and provides useful information to stakeholders,

lowers the cost of capital, and reduces information asymmetry. There has been limited

research on whether forces attributable to institutional theory are capable of influencing

banking operational behaviour, and more specifically, even more limited research on

this topic in developing economies. As mentioned earlier, the institutional setting of a

developing country is different from that of a developed country. Examining the

association of corporate risk disclosure with financial performance warrants research in

a developing economy setting. This study goes one-step further by examining the

association of risk disclosure with banks’ operating performance and bank valuation.

Based on the above research objectives, the research questions posed in this study are:

Research Question 1: What is the extent of corporate risk disclosure and to what extent

did banks in Bangladesh respond to the development of international standards relevant

to risk and its disclosure (IFRS 7 and Basel II: Market Discipline)?

Research Question 2: What bank characteristics and/or institutional pressures act as

determinants for disclosure of risk?

Research Question 3: Does risk disclosure have an association with bank performance?

Based on the research questions above, Figure 1.2 depicts the framework for this

research.

9

1.4 Key terms

This section highlights the definitions of key concepts and terms that are used

extensively throughout this thesis. These are presented in Table 1.1.

Term Explanation

Risk Disclosure ‘If the reader is informed of any opportunity or prospect, or of any hazard,

danger, harm, threat or exposure, that has already impacted upon the

company or may impact upon the company in the future or of the

management of any such opportunity, prospect, hazard, harm, threat or

exposure’ (Linsley & Shrives 2006, p.389).

Risk Disclosure

Index

A comprehensive Risk Disclosure Index has been developed in this study

to examine the extent of risk disclosure by listed banks in Bangladesh.

This benchmark set is based on international standards (IFRS 7 and Basel

II: Market Discipline) and an extensive list of risk disclosure items from

key previous studies. The Risk Disclosure Index consists of 147 specific

risk items in seven categories.

2Figure 1.2: Depiction of the framework for this research

1 Table 1.1: Key terms

Research Question 1 Research Question 2

Research Question 3

The extent of risk disclosure in annual

reports

Determinants of risk disclosure

Association of risk disclosure with

performance

10

Term Explanation

Voluntary and

Mandatory

disclosures

Mandatory disclosure: Any disclosure that is required by law,

accounting principles, or regulatory agencies’ regulations are

mandatory disclosure (Hassan & Halbouni 2013).

Voluntary disclosure: Any disclosure that is not classed as mandatory.

In the absence of mandatory requirements under the Bangladesh Bank

Company Act 1991 (amended in 2003), or the Companies Act 1994,

International Financial Reporting Standards (IFRS) or Bangladesh

Accounting Standards (Bangladesh Financial Reporting Standards), it is

argued in this thesis that risk disclosure effectively is voluntary for listed

banking institutions.

Determinants The key underlying factors in relation to risk disclosure in this study are

based on two underpinning theories (agency theory and neo institutional

isomorphism).

Performance Bank performance is measured using two aspects; bank operating

performance (e.g. financial performance, employee efficiency, solvency

efficiency and deposit concentration) and bank valuation (Tobin’s q and

book-to market ratio).

Global financial

crisis (GFC)

The GFC (2007-2008) raised significant concern in relation to corporate

risk disclosure as large numbers of financial institutions collapsed in the

U.K (RBS and HBOS), in the U.S (Citigroup, Lehman Brothers, Merrill

Lynch, and also in other European Countries (Dexia, Hypo RealEstate

and UBS). In Bangladesh, there is growing evidence that the post- GFC

(2007-2008) impacts are manifested in declining exports, declining

migration of labour, a growing number of sick industries, industrial

unrest, and reduced growth (Bangladesh Bank 2013b).

1.5 Research approach

As mentioned earlier, three interrelated Phases examine the research questions involved

in this study. The research method employed is detailed in Chapter 6. As shown in

Figure 1.3, Phase One of this study, presented in Chapter 7, investigates the extent of

risk disclosure of all listed banks on the Dhaka Stock Exchange in Bangladesh over a

11

seven-year period (2006-2012). In this Phase, the research involves the development of

a Risk Disclosure Index consisting of 147 specific risk items in seven categories, crafted

from international standards (IFRS 7 and Basel II: Market Discipline) and previous

studies. This Index is used as the criteria or benchmark against which to investigate,

using content analysis, the extent of risk disclosure practices within 30 listed

Bangladesh banks’ annual reports from 2006-2012 inclusive.

Phase Two of this study is presented in Chapters 8, 9 and 10. While the first Phase

identifies the disclosure practices within annual reports of banking institutions in

Bangladesh, the second Phase examines the determinants of risk disclosure. Based on

qualitative data from semi-structured interviews with banking regulatory representatives

together with quantitative data from annual reports that is informed by the Risk

Disclosure Index, Ordinary Least Squares regression analysis is used.

The third and final Phase of this study is discussed in Chapter 11. The results from the

Phase One (Risk Disclosure Index score) lead to an investigation of any potential

association of risk disclosure in relation to bank performance. To achieve this objective,

3 Figure 1.3: Research purpose and the three Phases

Phase One Phase Three

Phase Two

Purpose: Identify extent of risk

disclosure

Research Type: Descriptive

Method: Content Analysis

Data: Qualitative and Quantitative

Purpose: Identify the determinants of

risk disclosure

Research Type: Explanatory and

Exploratory

Method: Semi-structured interviews

and Multiple Regression

Data: Qualitative and Quantitative

Purpose: Examine the association of risk

disclosure with bank performance

Research Type: descriptive and predictive

Method: Multiple regression

Data: Quantitative

12

this Phase utilises primarily quantitative financial data from the annual reports of the

banks within this study.

1.6 Research contribution

The study contributes to the literature in several ways; First, in an attempt to redress in

part the empirical scarcity in risk disclosure studies in South Asian developing

countries, this study is the first to provide knowledge of corporate risk disclosure

practices and their underlying factors. Second, it helps assess the impact of new

international standards upon the extent of risk disclosures in a weak economic period

(GFC) and beyond. Third, a comprehensive Risk Disclosure Index is developed based

on international standards and is used as a benchmark against which to score actual risk

disclosures. The Risk Disclosure Index constructed in this study is of relevance to

financial institutions seeking to provide information for stakeholders and, indeed, to all

relevant parties seeking to assess or evaluate information in relation to risk disclosure.

To the researcher knowledge, the Risk Disclosure Index developed in this study is the

first, developed for the banking industry. Finally, the Risk Disclosure Index could be

used as a guideline for corporate risk disclosure in financial reporting and could be

used as an early warning system for banking institutions in any country. In addition, the

Risk Disclosure Index, developed in this research, contributes to the literature by

quantifying the extent of risk disclosure and identifying the factors determining them.

Stakeholders, particularly depositors and investors, can use this Index in selecting

their bank of interest. A detailed discussion on research contribution is presented in

Chapter 12.

1.7 Thesis outline

Figure 1.4 depicts the structure of the study and reveals that it is organised in Five Parts.

Part One comprises three Chapters. Chapter 1, this Chapter, describes the significance

of the study, research objectives and research questions, the approach, and thesis

structure. Chapter 2 introduces risk disclosure as an issue of concern and overviews the

regulatory framework and institutional arrangements for developing a risk-reporting

framework. Chapter 3 presents the contextual background and explains the major

impetus for selecting Bangladesh as the location for this study.

13

4Figure 1.4: Structure of the thesis

Part One: Introduction and research background

Chapter 1 presents an introduction to the research study

Chapter 2 provides the background to risk disclosure concerns

Chapter 3 presents the background context of Bangladesh as the location for the study

Part Two: Literature Review and Theoretical Underpinning

Chapter 4 presents previous studies on corporate risk disclosure

Chapter 5 presents the theoretical framework, conceptual framework and development

of Hypotheses

Part Three: Methodology

Chapter 6 presents the research methodology adopted. Data collection techniques are

described in this Chapter also

Part Four: Analysis and results

Phase One

Chapter 7 reports on the content analysis of sample banks’ annual reports

Phase Two

Chapter 8 presents the thematical discussion using qualitative interview data in relation

to the determinants of risk disclosure

Chapter 9 reports the descriptive results prior to further analysis of quantitative data

Chapter 10 reports the multiple regression results for the model adopted to investigate

the association between risk disclosures and their potential determinants

Phase Three

Chapter 11 presents the multiple regression results for the model developed to examine

the association between risk disclosure and bank performance

Part Five: Conclusion

Chapter 12 comprises a summary of the findings, implications, limitations, and

recommendations for future research

14

Part Two consists of two Chapters, Chapters 4 and 5. Chapter 4 reviews relevant

literature. This Chapter also identifies gaps in the literature addressed by this study and

the applicability of risk disclosure practices within developing country contexts.

Chapter 5 presents the theoretical framework for this study and provides justification for

and an overview of the theoretical framework (agency theory and neo institutional

isomorphism) underpinning this research. This Chapter introduces the conceptual

framework underpinning this study also.

Part Three explains the methodology used in this study. Chapter 6 describes the

research design, sample, research instruments and analytical techniques and approaches.

As the research objectives of this study support a mixed method approach, the Chapter

explains both qualitative and quantitative methods of data collection and analysis

techniques. Part Four presents analysis of the data gathered from annual reports and

interviews. Chapter 7 presents the content analysis of data elicited from annual reports,

Chapter 8 thematically analyses the qualitative data and Chapters 9, 10 and 11 present

the quantitative data analysis using statistical techniques such as multiple regression.

The final Part presents the research findings, conclusions and implications. Chapter 12

provides the conclusions relating to risk disclosure practices, their determinants and

performance by banks in Bangladesh. The thesis concludes with the summary of the

findings, the research limitations and ideas for further potential research are provided.

15

CHAPTER 2: Risk Reporting as an Issue of Concern

2.1 Introduction

The primary objective of this Chapter is to introduce the issue of risk reporting as a

corporate and regulatory concern. This Chapter presents a background to and overview

of risk reporting to provide an explanation of corporate risk reporting practice.

Shareholders and other stakeholders desire banks to disclose both financial and non-

financial information for related investment, credit and other decisions. To fulfil

stakeholders’ demands effectively, financial reporting has been improving and

increasingly communicating information with regard to risk profile (Beretta & Bozzolan

2004). Moreover, the demand by stakeholders for risk reporting has been increasing

after the GFC of 2007-2008 (Lajili 2009; Michael, Kaouthar & Daniel 2011).

Before turning to discussion of the background contextualisation of Bangladesh in the

next Chapter, this Chapter addresses the key concepts underlying the research questions

identified in Chapter 1. Figure 2.1 depicts the structure of this Chapter as follows.

2.2 Background to risk reporting

Risk reporting has been of increasing importance in international policy arenas and

raised significant interest around the world (Aebi, Sabato & Schmid 2012). The


Introduction (2.1)

Background to risk

reporting (2.2)

Overview of

institutional setting

(2.4)

Policies, pressures

and corporate

response (2.3)

Risk disclosure as a

major concern in

Bangladesh (2.5)

Chapter conclusion

(2.6)

16

increasing complexity of business and need for transparency create demand for clarity

in disclosing companies’ risk profiles, risk management and risk monitoring processes

(Michael, Kaouthar & Daniel 2011). Hassan and Halbouni (2013) argue that annual

reports should provide the integral business process that communicates between the

company and key stakeholders as to whether stakeholders’ concerns have been

understood by the company. This section highlights the characteristics of the business

environment that create demand for risk disclosure and motivates regulators and

accounting professionals to enhance the quality of reporting.

2.2.1 Changes in business environment and emergence of risk reporting

The business environment has changed dramatically over the past decade, driven by

technological advancement, globalisation of markets and concentration of power in

market investors (Albrecht & Sack 2010). These changes make the business

environment more demanding for stakeholders to comprehend and similarly so for

business information without complete accompanying explanations (Beretta &

Bozzolan 2004). Figure 2.2 highlights the factors affecting reporting by companies.

Technological advancements such as computers, the internet, and data transmission

software have simplified the development of business, thereby creating opportunities

and challenges for companies. Such technological advancement has made it easier for

companies to communicate with investors. Additionally, globalisation of business has

allowed the world to become one giant marketplace with increased availability of

competitive information (Albrecht & Sack 2010). Given the differences in legal, social

and economic circumstances in different countries and also the differences in need for

accounting information among users of financial information, there have been calls by

international standard setters to harmonise accounting standards related to the

preparation of financial reporting (Beretta & Bozzolan 2004). Particularly, the

international harmonisation of accounting practices has been a central concern for

companies operating in more than one country (Marshall & Weetman 2002).

17

Source: Adapted from Albrecht and Sack (2010)

Albrecht and Sack (2010) argue that the combined forces of technology, globalisation

and market power have increased competition, regulation, financial volatility and the

level of uncertainty about business entities. Consequently, shareholders and other

stakeholders want listed companies to disclose financial as well as non-financial

information in relation to companies’ future performance (Albrecht & Sack 2010;

Beretta & Bozzolan 2004). In this sense, Beretta and Bozzolan (2004, p. 266) argue

that ‘listed companies have been improving the communication of their long-term

value-generation capabilities by increasing the amount of information disclosed with

regard to the risks faced and their expected impact on future profits’.

Moreover, many organisations have adopted rapid business expansion through either

internal development or mergers and acquisitions (Hill & Short 2009). However, such

expansion raises many challenges and concerns for investors. In addition, companies are

being confronted with frequent change in laws and regulations (Barth, Caprio Jr &

Levine 2004). Complying with these regulations is sometimes costly and adversely

affects companies’ operating cost and performance. Therefore, extant research argues

that corporate risk disclosure could be an effective monitoring system because it

provides a greater transparency and increases investors’ confidence in their decisions

6Figure 2.2: Factors affecting financial reporting

Drivers

Changes

- Technology

- Globalisation

- Concentration of Market Power

- Increased competition - Increased regulation - Financial volatility - Concentrated Market Power - Increasingly complex business - Better, quicker, and more decisive strategic actions by management - Increased focus on customer satisfaction

-Increased uncertainty and the explicit recognition of

risk

Demand for risk reporting Results

18

(Cabedo & Miguel Tirado 2004; Linsley & Shrives 2006; Solomon et al. 2000).

Deumes and Knechel (2008) argue that risk disclosure creates corporate transparency

for well-functioning markets and brings general gains in economic efficiency.

2.2.2 Risk reporting as an issue of concern in banking institutions during

financial crises

A large number of financial institutions collapsed during the GFC of 2007-2008 and

that raised significant concern in global credit markets about their performance and risk

governance (Erkens, Hung & Matos 2012; Fahlenbrach & Stulz 2011). Thereafter,

some studies have examined the performance of corporate governance and additional

attention has been paid to banks’ risk management (Adams 2012; Bebchuk 2010;

Beltratti & Stulz 2012; Erkens, Hung & Matos 2012).

Banking crises have been a common phenomenon throughout history; indeed banks are

at the centre of financial crises (Barth & Landsman 2010). To some extent, banking

crises are like periodic events that ‘unexpectedly emerge from the earth’ (Laeven 2011,

p.18). Reinhart and Rogoff (2013) count 268 banking crises over the period from 1800

through to 2008. Bordo et al. (2001) revealed that the frequency of banking crises has

been increasing in recent decades. According to Reinhart and Rogoff (2013, p.4557)

‘the historical frequency of banking crises is quite similar in high- and middle-to-low-

income countries, with quantitative and qualitative parallels in both the run-ups and the

aftermath’. The National Commission on the Causes of the Financial and Economic

Crises in the U.S. (2011; p. xvii) concluded that ‘dramatic failures of corporate

governance ….at many systematically important financial institutions were a key cause

of financial crises’.

The lack of risk management and failure of governance mechanisms are cited

commonly as the key contributing factors to the GFC of 2007-2008 (Aebi, Sabato &

Schmid 2012; Beltratti & Stulz 2012; Diamond & Rajan 2009; Hashagen, Harman &

Conover 2009; Strebel 2009). These raise several questions for regulators with respect

to corporate governance and banks and for testing the value of ‘risk governance’ and

19

‘corporate governance’ (Aebi, Sabato & Schmid 2012; Fahlenbrach & Stulz 2011).

Bebchuk (2010) suggests that excessive risk taking in the financial sector performed a

key role in the financial crisis of 2007-2008. Beltratti and Stulz (2012) argue that banks

with poor governance were involved in excessive risk taking responsible for huge losses

during the financial crisis. Goddard, Molyneux and Wilson (2009, p. 363) report ‘an

estimation of $2.7 tn (trillion) for write downs of the US – originated assets by banks

and other financial institutions between 2007- 2010 and the estimated write downs for

all mature market-originated assets for the same period are in the region of $4tn

(trillion).’

Accordingly, the financial crisis of 2007-2008 led to a slowdown in the global economy

and a further awareness of and need for appropriate risk governance structures within

banking institutions (Aebi, Sabato & Schmid 2012). It is logical that banks that identify

and analyse risks earlier than their business counterparts will be better positioned to

avoid or mitigate potential risks and can create value for investors by fostering

understanding of the risk profile of invested businesses. For example, Solomon et al.

(2000) found stakeholders strongly demand corporate risk disclosure to improve their

investment decisions. Beretta and Bozzolan (2004) argue that effective risk

communication minimises investment risks and builds opportunities for stakeholders.

Therefore, annual reporting of risk is needed to make available worthwhile disclosure to

stakeholders in making their investment decisions (Milne 2002).

2.3 Risk disclosure related policies, pressures and corporate responses

The perceived importance of corporate risk disclosure as a major financial reporting

issue has been highlighted by increased global interest, debate and discussion on the

issue of risk reporting among stakeholders since the GFC (Michael, Kaouthar & Daniel

2011). Concerns about corporate risk disclosure led bank supervisors and regulators to

rethink the rationale of banking regulations in providing transparent information and

building stakeholders’ confidence (Lajili 2009).

20

Several academic and professional reports (AICPA 1995; IASB 2007; ICAEW 1995;

Schrand & Elliott 1998), particularly in the U.S.A., U.K. and other European countries,

demand for inclusive risk information in financial reports. Acknowledging the

importance of risk disclosure, standard setters have enhanced regulatory reforms in

recent years; such as by issuing International Financial Reporting Standard 7 [Financial

Instruments: Disclosures] (IFRS 7) and BASEL II: Market Discipline, to govern

accounting practices and disclosure. Internationally, to date, the most advanced risk

disclosure regulations exist in the U.S.A., Canada, U.K and Germany (Michael,

Kaouthar & Daniel 2011). These countries require and enforce risk information in both

the notes to financial reports and supplementary management reports.

In the U.S.A., Financial Reporting Release No 48 ‘Disclosure of Accounting Policies

for Derivative Financial Instruments and Derivative Commodity Instruments and

Disclosure of Quantitative and Qualitative Information about Market Risk Inherent in

Derivative Financial Instruments, Other Financial Instruments, and Derivative

Commodity Instruments’ (FRR 48) was issued in 1997. This document requires

Securities and Exchange Commission enlisted companies to disclose market risks in the

notes and in the Management reports. Listed companies in Canada also apply FRR 48

to disclose risk information in the Management Discussion and Analysis (MD&A)

section. In the U.K, the Operating and Financial Review (OFR), issued in 1993,

necessitates disclosure of information about key risks. The Australian Securities

Exchange (ASX) issued its first version of Corporate Governance Principles and

Recommendations in 2003 (amended in 2007 and 2010) where Principle 7 pertains to

risk management and recognition. These events provide evidence of the increasing

importance of risk disclosure as measure of good corporate governance practices.

Nonetheless, from a regulatory viewpoint, the status of risk reporting is piecemeal in

nature, focusing mainly on market risk (Amran, Bin & Mohd 2008; Beretta & Bozzolan

2004; Michael, Kaouthar & Daniel 2011). Additionally, domestic regulations in each

country take different approaches in requiring disclosure of risk information. For

example, both the U.S.A. and Canada require disclosure of market risk, including

forward-looking information (FRR 48). However, in Canada, disclosure of qualitative

21

types of information is voluntary and is guided by the Ontario Securities Commission

(Michael, Kaouthar & Daniel 2011). The importance of risk reporting has been

increasing in the last decade (Bordo et al. 2001; Lajili 2009; Reinhart & Rogoff 2013).

However, regulatory bodies provided less attempt to make available for an explicit and

combined risk disclosure outline. In this study, a comprehensive Risk Disclosure Index

is developed for the analysis of risk information provided within annual reports. To the

researchers’ knowledge, this Index is the first integrated instrument developed to

quantify recommended risk disclosures for the banking industry.

2.4 An overview of the institutional arrangements and accounting

regulations in developing a risk reporting framework

Several professional and institutional reports worldwide highlight the importance of risk

reporting and call for comprehensive disclosure of risk information to satisfy the users

of financial reports. This section documents the evolution of thinking on risk and risk

disclosure by professional and institutional bodies in developing a risk reporting

framework.

2.4.1 Cadbury Report (1992)

In the U.K., the issue of corporate risk reporting attracted mainstream public attention in

the 1990s, leading to the Cadbury Report in 1992. After establishing the Cadbury

Committee in 1991, the Financial Reporting Council (U.K.) and the London Stock

Exchange issued the Cadbury Code in 1992, which included best practice code and

recommended the code for adoption by the London Stock Exchange enlisted companies.

The code in the Cadbury Report centred attention in four major areas: ‘the board of

directors’; ‘non-executive directors’; ‘executive directors’; and ‘control and reporting’.

This Report recommended the disclosure of risk information by companies as part of

reforming corporate governance and suggested improvements in disclosure about

internal controls. The European Union, the U.S.A. and the World Bank adopted this

recommendation also (Linsley & Shrives 2000).

22

2.4.2 The American Institute of Certified Public Accountants (AICPA)

With an aim to improve financial reporting, the American Institute of Certified

Accountants (AICPA) proposed a comprehensive business-reporting model focusing on

risk disclosure. The model included information that forecasts future events and focuses

attention on non-financial information. The Jenkins Report (AICPA 1994) followed the

Cadbury Report (1992) and recommended that business reports should include

information about risk and opportunity to facilitate analysis of each business segment

separately and identify the diverse opportunities and risks.

2.4.3 The Institute of Chartered Accountants in England and Wales

Financial risk reporting is the foundation for accounting and business practices as it

builds an early warning system into the existing management information system

(ICAEW 2010b). The Institute of Chartered Accountants in England and Wales

(ICAEW) in 1997 issued a discussion paper on business risk proposing listed companies

be at the forefront of improving risk disclosure in annual reports, including disclosure

about relevant measures of risks and actions to manage risks. It concentrated on forward

looking information disclosure to help investors to forecast in the longer run.

Subsequently, the ICAEW and London Stock Exchange agreed to provide guidance for

board of directors on implementing internal control. As a result, the Turnbull Report

(1999) was published titled ‘Internal control: Guidance for directors on the combined

code’. The Report emphasised that ‘a company’s system of internal control has a key

role in the management of risks that are significant to the fulfilment of its business

objectives (Para. 10)’. In conjunction with guidance on risk and control mechanisms,

the Turnbull Report focused on risk assessment, the control environment and control

activities over risks, information and communication of risk and monitoring activities.

The Turnbull Report thus highlighted the link between internal control and risk

(Abraham & Cox 2007). The Turnbull Report viewed the advantages of providing key

business risk information from several aspects; first, practical information; second,

23

reduced cost of capital; third, better risk supervision; and fourth, maintenance of

improved accountability towards stakeholders (Wallage 2000).

Highlighting users’ demands for risk information, sources, assumptions, determining

factors and alternative outcomes of uncertainties, the ICAEW published another report

in 2003 (ICAEW 2003). The report focused on disclosure of prospective financial

information and the factual representation of business risk analysis. The demand for

improved risk reporting intensified in GFC (2007-2008) period, (e.g. Dobler, Lajili &

Zéghal 2011; Uddin & Hassan 2011) the ICAEW published reports in 2010 highlighting

lessons from the crisis for banking institutions (ICAEW 2010a). The report mentioned

that:

Risk information is often presented in a piecemeal manner in bank annual reports,

spread between the audited financial statements and the unaudited front sections. Banks

need to focus on clearer presentation, which allows users to understand the big picture,

which is currently often obscured by the volume of detailed information. Summary risk

statements are a potential way of providing this big picture (p.4).

The report suggested increasing transparency and stakeholders’ confidence in financial

reporting. The report further suggested that directors disclose the governance policies

and risk management practices of the company.

Next, the ICAEW (2011) identified the key challenges for risk reporting: inherent

unreliability, costs exceeding perceived benefits and generic disclosure. Inherent

unreliability occurs as judgement about risk information is subjective. The report

recommended seven principles for better risk reporting; providing useful information

for assessing business risks, disclosure of detailed qualitative information, integration of

risk information with forward looking information along with broader context, thinking

beyond the annual reporting cycle of risk information, keeping a list of principal risks,

highlighting current concerns and reviewing risk experiences.

24

2.4.4 Hampel Report (1998)

The Hampel Report titled ‘Committee on Corporate Governance’ published in the U.K.

in 1998, revised the corporate governance system there after implementation of the

Cadbury Report in 1992. The concept of internal control used in the Cadbury Report is

explained more elaborately in the Hampel Report, addressing business risk assessment,

agreement with regulations and maintenance of assets, including the minimising of

fraud.

2.4.5 Higgs Report (2003) and Smith Report (2003)

The Higgs Report (2003) titled ‘Review of the role and effectiveness of non-executive

directors’ revised the Cadbury Report, providing recommendations for board

composition and emphasising risk assessment and risk management. The Report argues

that ‘the board’s role is to provide entrepreneurial leadership of the company within a

framework of prudent and effective controls which enable risk to be assessed and

managed’ (p.21). In addition, in terms of specifying the responsibilities of the non-

executive director, the Report noted: ‘non-executive directors should satisfy themselves

that financial information is accurate and that financial controls and systems of risk

management are robust and defensible’ (p.27). Furthermore, the Smith Report (2003)

titled ‘Audit Committees Combined Code Guidance’ suggested that the board establish a

separate risk committee to assess the scope and risk management systems of the

organisation to identify, assess, manage and monitor financial risk.

2.4.6 International Financial Reporting Standards (IFRS)

The Financial Accounting Standards Board (FASB) in the U.S.A. and the International

Accounting Standards Board (IASB) in the U.K. require risk disclosures for users of

annual reports in making their investment decisions. As mentioned in in Chapter 1,

International Financial Reporting Standard 7 (IFRS 7) [Financial Instruments:

Disclosures] was issued by the IASB in 2005 to became effective in January 2007.

IFRS 7 sets guidelines for enhancing financial disclosure and, when adopted and

25

enforced, requires disclosure of risk information arising from financial instruments2 in

financial reports (IASB 2007).

Furthermore, IFRS 7 seeks provision of information in relation to companies’ financial

performance, the associated risk of financial instruments and the risk management

policies (IASB 2009). IFRS 7 includes financial instrument disclosure requirements for

all companies under one standard as it incorporates the disclosure requirements

regarding financial instruments which were previously set out in IAS 30 (Disclosure in

the Financial Statements of Banks and Similar Financial Institutions) and IAS 32

(Financial Instruments: Presentation). IFRS 7 states that ‘an entity shall disclose

information that enables users of its financial statements to evaluate the nature and

extent of risks arising from financial instruments to which the entity is exposed at the

reporting date’ (Para. 7.31).

IFRS 7 requires minimum disclosure of qualitative and quantitative information about

market, credit and liquidity risk information (IASB 2007). The ‘qualitative disclosures

describe management’s objectives, policies and processes for managing those

risks…(and) the quantitative disclosures provide information about the extent to which

the entity is exposed to risk, based on information provided internally to the entity’s key

management personnel’ (IASB 2007, Para IN 5b).

After the GFC (2007-2008), the IASB issued several amendments to IFRS 7. The first

being in October 2008 permits reclassification of some financial instruments. The next

amendment in 2009 introduced a three level hierarchy for fair value measurement

disclosure to improve comparability between companies and strengthen the disclosure

about liquidity risk associated with financial instruments (assets and liabilities) (IASB

2009). However, these amendments were controversial as fair value was argued to hide

the real risks to which companies are exposed and increase the mistrust by stakeholders

(Judge, Douglas & Kutan 2008). In addition to that, reclassification of financial assets

2‘In banking institutions, financial instruments comprise most of the assets and liabilities (IASB 2007).’

26

amendments was controversial as the changes were seen as political3 and were adopted

without due process (Laux & Leuz 2009).

2.4.7 BASEL II: Pillar 3 (Market Discipline)

The Basel Committee on Banking Supervision (BCBS)4 is a forum for regular

cooperation on banking supervisory matters. The Basel Committee consists of

representatives from Central Banks and regulatory authorities around the world.

Member countries implement recommendations by the Basel Committee through their

national laws and regulations. The Basel Committee requires banks to disclose risks

under a capital adequacy and market discipline framework. Since 1974, the BCBS has

worked to enhance understanding of key supervisory issues and improve the quality of

banking supervision all over the world. In 1988, it published the first global banking

guideline for capital adequacy (BASEL I) with two major aims; first, to support the

trustworthiness and firmness of the worldwide banking system and second, to achieve

fair and consistent practices among international banks (Basel 2003).

Basel I required banks to hold a minimum capital reserve based on their owned assets,

the base for capital with Tiers; such as, Tier 1 consisting of common equity and

preferred stock and Tier 2 comprising subordinated debt and hybrid instruments.

BASEL I weaknesses in calculating the ratio of risk weighted assets were overcome by

Basel II in 2004, which developed a framework to further strengthen the soundness of

banking institutions (Barth, Caprio & Levine 2004).

3 According to Bischof, Brüggemann and Daske (2010, p.1) ‘these (IFRS 7) amendments leave

commercial banks reporting under IFRS with the choice to retroactively reclassify financial assets that

were previously measured at fair value into categories which require measurement at amortized cost, i.e.

to effectively suspend fair value accounting for these assets. This decision sharply contrasted the IASB’s

general strategy in reporting for financial instruments and its strong initial position against

reclassifications. However, the board eventually surrendered to severe political pressure by the EU

Commission and EU leaders’. 4 The BCBS was established in 1974 comprising representatives from Central Banks and supervisory

authorities of the Group of Ten countries (Belgium, Canada, France, Germany, Italy, Japan, Netherlands,

Sweden, Switzerland, United Kingdom, United States and Luxembourg). The Committee meets at the

Bank for International Settlements, Basle, Switzerland. To date, it comprises 27 countries worldwide,

including Bangladesh.

27

The Basel II framework features three ‘Pillars’, comprising minimum capital

requirements (Pillar 1), supervisory review processes through governance of banks

(Pillar 2) and market discipline (Pillar 3). Pillar 1 includes minimum capital

requirements and Pillar 2 provides risk management guidance with respect to banking

institutions in relation to interest rate, credit risks and operational risks. The aim of the

second pillar in the framework is to make sure sufficient capital to maintain all risks and

encourage banks to improve better monitoring techniques to manage their risks (Basel

2012).

In conjunction with Pillar 1 and Pillar 2, Pillar 3 aims to improve market discipline5 by

providing disclosure guidelines for capital adequacy, risk exposure and risk assessment

process information provided to market participants (Basel 2012; Ismail, Rahman &

Ahmad 2013; Nier & Baumann 2006). The market discipline framework can act as a

regulatory tool by providing for the information needs of an effective capital market

(Barth & Landsman 2010). In 2006, the Basel Committee revised the Basel II

framework to encourage stronger risk management practices in the banking industry.

Pillar 3 disclosure requires both quantitative and qualitative information (Basel 2006).

Nier and Baumann (2006) showed three conditions that should be satisfied to achieve

market discipline; first, investors’ consideration about the risk of default by banks,

second, market responses to banks’ risk profiles and the cost benefit for banks and their

managers, and third, adequate information to determine the riskiness of banks.

After the GFC of 2007-2008, the Basel Committee promoted the adoption of sound

corporate governance guidance practices in the banking sector, stating that ‘risk

reporting systems should be dynamic, comprehensive and accurate and should draw on

a range of underlying assumptions’ (Basel 2010, p.22). They also suggested that by

engaging an internal auditor, the board and senior management can identify the risk

management process and improve the quality of risk reporting (Basel 2010).

5 According to Basel Committee (2001, p.4) ‘market discipline enforces supervisory efforts to promote

safety and soundness in banks and financial systems. It describes the bank’s objective and strategy for the

public disclosure of information on its financial condition and performance’.

28

To develop a more resilient banking sector and as a feedback to the GFC, the Basel

Committee programmed Basel III6 to be implemented from 2013 until 2019. Basel III

introduced an additional capital buffer and a minimum leverage ratio and liquidity

coverage ratio. The examination of Basel III is beyond the scope of this study. At

present, Basel II: Market Discipline (Pillar 3) contains the most specific disclosure

framework to communicate risk exposure and risk assessment in banking institutions

internationally.

The timeline for this present study lends to its importance, coming as it does a few years

after the publication and implementation of IFRS 7 and its amendments and BASEL II:

Market Discipline. In the Bangladesh context, it is expected that risk disclosure would

be increased as an evidence of and endorsement towards corporate governance

improvements (Solomon et al. 2000). This research hypothesises that banks will

respond to these international standards by enhancing the extent of risk disclosure even

where compliance is not compulsory as in a country such as Bangladesh.

2.5 Risk disclosure as a major concern in Bangladesh

A growing number of studies argue that accounting and reporting systems in developing

countries differ significantly from those in developed countries (Hassan 2009; Khan

2013; Mir & Rahaman 2005; Wallace & Naser 1995). Such studies revealed that the

institutional setting, accounting technologies, the regulatory framework and rules in

developing countries differ from those in developed countries. The institutional setting

of any country depends on factors including political, social and historical (Prowse

1998).

Bangladesh is an emerging7 economy. According to Farooque et al. (2007, p.130)

‘Corporate governance systems here [i.e. in Bangladesh] are arguably less evolved than

6 In the aftermath of GFC (2007-2008), Basel Committee revised existing capital adequacy framework

and issued Basel III : Capital and their liquidity requirements in November 2010. 7 According to Khan, Muttakin and Siddiqui (2013, p.208) ‘in 2005, Goldman Sachs, the global asset

management company, classified Bangladesh as one of the ‘next 11’ emerging economies for its high

potentials, along with the BRIC countries, to be the largest economies in the twenty-first century

29

those in developed countries’. The institutional setting in Bangladesh has been inherited

from 200 years of British colonial rule. The regulatory settings in Bangladesh were

impacted by the British governing settings and the political oppression for 23 years

during the Pakistani period. The next Chapter provides a more detailed analysis of

Bangladesh. According to Farooque et al. (2007), these two periods have impacted the

institutional settings along with the political and economic environment.

The 200 years of British colonial rule has twin impact…on the one hand, it allowed

Bangladesh to inherit an English-style institutional and regulatory framework,

Westminster-style parliamentary democracy, a judiciary independent of the legislature

and the executive wings of the government, and a highly powerful and insensitive

bureaucracy. On the other hand, the prolonged economic exploitation and political

domination coupled with the creation of crony elite subservient to the expatriate rulers

contributed to institutionalizing corruption in the bureaucracy, creating only a limited

pool of entrepreneurs, and inhibiting development of a broad based capital market. The

23 years of internal colonization during the Pakistan period also saw a continuation of

political suppression and economic negligence….. did not allow the country….. to build

capital market institutions (p.131).

The country continues to experience weak institutional settings in the form of highly

concentrated ownership structures (such as family owned or controlled substantial

shareholdings of businesses) and a weak capital market, along with poor legal structure

(Khan, Muttakin & Siddiqui 2013). A Bangladesh Enterprise Institute (2003) survey

provided evidence that family members dominate the boards of 73 per cent of listed

companies. In Bangladesh, the closely held family members on the board often become

advisors to internal auditors without much technical and specialised knowledge (Hopper

et al. 2003). Moreover, the legal system in Bangladesh is poor in its ability to oversee

corporate affairs (Belal, Cooper & Roberts 2013; La Porta, Lopez-De-Silanes &

Shleifer 1999). Additionally, the Bangladesh Securities and Exchange Commission has

scant resources in terms of technical, personnel and logistic support to monitor

(http://www.goldmansachs.com)’. BRIC countries are Brazil, Russia, India and China.

http://www.goldmansachs.com)/

30

disclosure of financial reporting (Khan 2004). In Bangladesh, disclosure practices in

annual reports operate within a framework of different regulations, laws and guidelines;

some mandatory, some merely recommended (Belal 2001). These are namely the

Companies Act 1994, the Bank Company Act 1991 (for banking institutions), the

Insurance Act 1938 (for insurance companies), the Income Tax ordinance, 1984 (for all

companies and public enterprise).

The Bangladesh Bank Order 1972, the Bank Company Act 1991 and the Companies Act

1994 regulate annual reporting by banking institutions in Bangladesh. The external

corporate audit is governed based on the Bangladesh Chartered Accountants By-laws

1973. The Bangladesh Bank Order 1972 and the Bank Company Act 1991 mandate

banks to provide audited balance sheets and profit and loss accounts (with working

papers) to Bangladesh Bank (the Central Bank), the Registrar of Joint Stock companies

and to publish these documents annually. The Companies Act 1994 requires that

companies should provide the annual report in a prescribed form and audited by a

chartered accountant. However, the Act does not necessitate mandatory compliance

with adopted accounting standards. In the absence of mandatory requirements by

company law or the Bank Company Act 1991, compliance with International Financial

Reporting Standards (IFRS) or Bangladesh Accounting Standards (Bangladesh

Financial Reporting Standards) is voluntary effectively for banking institutions, listed or

otherwise. The World Bank’s Report on the Observance of Standards and Codes (2003,

p.11) for Bangladesh noted the necessity for ‘the enactment of a new Financial

Reporting Act and the repeal of provisions on accounting, auditing, and financial

reporting in the Companies Act 1994, Bank Companies Act 1991, Insurance Act 1938,

and other related regulations’.

Extant studies have found that due to weak enforcement mechanisms, lack of auditor

independence and the perceived undemocratic nature of the International Financial

Reporting Standards (and their predecessors) implementation process in Bangladesh,

there is resultant low disclosure in annual reports (Mir & Rahaman 2005; Sobhani,

Amran & Zainuddin 2012). A team from the World Bank provided a systematic

assessment of strengths and weaknesses of accounting and auditing practices in

31

Bangladesh. They remarked ‘the accounting and auditing practices in Bangladesh suffer

from institutional weaknesses in regulation, compliance, and enforcement of standards

and rules. The preparation of financial statements and conduct of audits, in many cases,

are not consistent with internationally acceptable standards and practices’ (World Bank

2003, p.3). Despite this, auditors issued unqualified audit reports on these annual reports

(Mir & Rahaman 2005).

Apart from this, the financial sector perceives increasing non-performing loans, low

recovery rates, operational weaknesses, excessive political, government and owners’

interference, substandard accounting and audit quality and a weak regulatory

supervisory role (World Bank 2003; Khan et al. 2011; Uddin & Choudhury 2008b).

Therefore, examining risk disclosure in a weak regulatory environment (such as

Bangladesh) are likely to provide greater insights to risk disclosures and their

determinants because little variation could be expected in mandated disclosures within a

highly regulated environment with effective enforcement. Hence, corporate risk

disclosure, particularly in the banking industry, warrants research significance. The goal

of this study is to fill the gap in the literature on risk disclosure using a sample of banks

from a developing country, Bangladesh, where the institutional setting creates, in effect,

voluntary rather than mandatory compliance with accounting and other standards of

public reporting of risk and performance.

2.6 Chapter conclusion

The objective of this Chapter is to provide evidence that the issue of corporate risk

disclosure has become of major concern. The discussion within this Chapter provides an

overview of corporate risk disclosure as an issue of concern during the financial crisis of

2007-2008, especially for financial institutions. It provides an overview of policies and

responses to institutional arrangements in relation to risk disclosure in the developing

country of Bangladesh. Thus, this Chapter builds the platform for a broader study that

investigates the disclosure of risk matters by banks in Bangladesh. Chapter 3

incorporates detailed discussion regarding the research context and provides the

motivation for selecting Bangladesh as the setting for this study.

33

CHAPTER 3: Bangladesh - the Context of the Study

3.1 Introduction

A rapidly growing economy resulting from increasing globalisation of various sectors,

increasing customer demand and growing competition, makes the banking sector of

Bangladesh an interesting research context. Since this study’s focus is on risk reporting

practices in the banking sector, it is essential to provide an overall picture of the

country’s banking sector in comparison with that of other countries, explain its

evolution and explain why Bangladesh creates an appropriate research setting. This

Chapter reviews the development of the accounting setting, the institutional background

and the country’s political, economic and social factors and provides an overview of the

development of banking institutions and risk reporting practices in Bangladesh. Figure

3.1 presents the structure of this Chapter as follows.

3.2 Bangladesh as the country of study

This section outlines the historical, political, socio-economic and regulatory setting for

disclosure practices in financial reporting in Bangladesh. Discussion of these contextual

factors is necessary in order to provide the background to this research and a thorough

understanding of risk reporting in Bangladesh.

7Figure 3.1 Roadmap of Chapter

Introduction (3.1)

Bangladesh as a

country of study (3.2)

Financial system in

Bangladesh (3.3)

Banking industry (3.4)

and financial reform in

banking sector (3.5) in

Bangladesh

Motivation for

choosing Bangladesh

as a context for the

study (3.6)

Motivation for selecting

listed banks in

Bangladesh (3.7) and

chapter conclusion (3.8)

34

3.2.1 Bangladesh: Country profile

The People’s Republic of Bangladesh is one of the largest deltas in the world with an

area of 147,570 sq. km. and one of the most densely populated (estimated 163.7M

July 2013, 8th

in world ranking8) countries in South Asia, situated on the Bay of

Bengal. Bangladesh became an independent and sovereign country in 1971 after a long

liberation war against Pakistan. The official language is Bengali (Bangla), however

English is widely used in educational institutions, the media and commerce. The capital

city is Dhaka with seven divisional cities (i.e. Dhaka, Khulna, Rajshahi, Chittagong,

Rangpur, Sylhet and Barisal). More than 75 per cent of the population live in rural

areas; however, urbanisation has been increasing rapidly over the last two decades9.

3.2.2 Political and historical context

The origin of Bangladesh dates back to during the remnants of civilisation in the greater

Bengal 4000 years ago (Xinhua 2006) when the region was settled by Dravidian,

Tibeto-Burma, and Austro-Asiatic peoples. In the 12th

century (AD), Bengal fell to

Muslim conquest from West India and a large part of Bengal was subjugated by Sultans

and Lords. By the 16th

century, The Mughal Empire controlled Bengal and Dhaka

became the important provincial centre of Mughal administration (Eaton 1996). At the

end of the 15th

century, European traders arrived in Bengal and formed the British East

India Company. Their control and influence grew following the Battle of Plessey in

1757 (Baxter 1998). The rebellion of 1857, known as the ‘Sepoy Munity’ led to

dissolution of the British East India Company. British colonial rule was over in 1947

with India and Pakistan partitioned under religious coverage. The political, economic

and linguistic discrimination led to liberation of East Pakistan from West Pakistan.

Bangladesh received independence after nine months of a liberation war under the

leadership of Bangabandhu Sheikh Mujibur Rahman.

8 https://www.cia.gov/library/publications/the-world-factbook/geos/bg.html

9 Bangladesh Bureau of Statistics (2013).

https://www.cia.gov/library/publications/the-world-factbook/geos/bg.html

35

After its independence, Bangladesh established a parliamentary democracy with Sheikh

Mujib as Prime minister. In August 1975, Sheikh Mujib and his family were

assassinated in a military coup and until 1990, Bangladesh was more or less under

military rule (Belal 2001); however, an active democratic parliament commenced in

1991. Since then two political parties, either the Awami League (AL) or the Bangladesh

Nationalist party (BNP), have ruled the country under democratic elections. A

democratic environment has had a positive impact on the economy of the country.

However, true democracy is not yet observed in Bangladesh (Belal 2001). Figure 3.2

presents a map of Bangladesh along with the national flag.

Source: http://www.lonelyplanet.com/maps/asia/bangladesh/

3.2.3 Economic context

The advantages of a mild, tropical climate and fertile soil helped Bangladesh develop as

an agrarian country; however, structural changes towards development of the

manufacturing and services sectors has increased in the past few years. Yet, 45 per cent

of people depend on the agricultural sector with rice as the staple crop10

. In addition,

extensive growth in the industrial and services sectors has contributed to the overall

economy of the country. In financial year 2012-13, growth in the agriculture, industrial

and service sectors was estimated at 2.54 per cent, 10.27 per cent and 6.16 per cent

respectively11

. The negative growth in the world economy due to the GFC slowed the

10

https://www.cia.gov/library/publications/the-world-factbook/geos/bg.html 11

Board of Investment Bangladesh (2014).

8Figure 3.2: The national flag and map of Bangladesh

http://www.google.com.au/url?sa=i&source=images&cd=&cad=rja&docid=lka1_Q-ypj2LNM&tbnid=6KXSRTBfZaduGM:&ved=0CAgQjRwwAA&url=http://www.flags.net/BNGL.htm&ei=NJ8kUv_BIojdkAW04ICIAw&psig=AFQjCNGxII2OmPobXaW7HzjECQfDFPfw2Q&ust=1378218164603530

http://www.google.com.au/url?sa=i&source=images&cd=&cad=rja&docid=lka1_Q-ypj2LNM&tbnid=6KXSRTBfZaduGM:&ved=0CAgQjRwwAA&url=http://www.flags.net/BNGL.htm&ei=NJ8kUv_BIojdkAW04ICIAw&psig=AFQjCNGxII2OmPobXaW7HzjECQfDFPfw2Q&ust=1378218164603530

http://www.google.com.au/url?q=http://www.lonelyplanet.com/maps/asia/bangladesh/&ei=bA0QU7vAEYewkgW8pIGwCQ&sa=X&oi=unauthorizedredirect&ct=targetlink&ust=1393562740289110&usg=AFQjCNH6r1BGsQglVc9TiTd1rzcXsKH-iA

https://www.cia.gov/library/publications/the-world-factbook/geos/bg.html

36

growth of the Bangladesh economy in financial year 2008-2009, although the average

growth remained above 6 per cent following the recession period12

. Bangladesh has

been affected post GFC through the reduction of remittances, migration, readymade

garments and agricultural exports (shrimp and tea) (Bangladesh Bank 2013).

The present environment of global competition and a free market economy highlights

the importance of private sector development in Bangladesh. The private sector

emphasis is on growth of the industrial and services sectors following the principles of a

market economy (Belal 2001). The government also accepts private sector management

as one of the key regulatory forces in achieving economic growth (Bhattacharya &

Chowdhury 2003). Several initiatives have been adopted and opportunities seized to

encourage private sector and overseas investors. Examples include publicly managed

enterprises being transferred to private ownership; administrative, infrastructure and

institutional facilities relating to business and industry facilities being increased through

establishment of different institutions; strengthening of the capital market through the

Dhaka and Chittagong Stock Exchanges and regulating the capital market through the

Bangladesh Securities and Exchange Commission.

Wages and salaries in Bangladesh remain the lowest in Asia for skilled workers13

. The

Japan External Trade Organisation surveyed 29 major cities in Asia and found

management remuneration grades in Dhaka to be two to three times less than in

Singapore, Shanghai and Bangkok. Further, renting industrial estate costs less than in

Shanghai, Jakarta or Bangkok and rental for both offices and housing, together with

transportation costs, are less expensive compared with other international cities (JETRO

2010). With youthful educated demographics, cheap labour, low business establishment

costs, advanced technology and economic growth, Bangladesh has a huge domestic

market. Table 3.1 presents statistics about the economy of Bangladesh.

12

Ministry of finance, Government of Bangladesh (2014). 13

The 20th Survey of Investment-Related Cost Comparison in Major Cities and Regions in Asia (JETRO

2010).

http://www.jetro.go.jp/en/reports/survey/pdf/2010_06_29_biz.pdf

37

Fiscal Year

1 July - 30 June

GDP total

US$112.00 billion (at current prices 2012-13)

GDP per capita

US$848 (at current prices 2012-13)

GDP growth rate (%)

6.32 (at constant prices 2012-13)

GDP composition

Agriculture: 17.5 per cent; industry: 28.5 per

cent; services: 53.9 per cent (2013 est.)

Total exports

US$24.287 bn (2012-13)

Total imports

US$35.44 bn (2012-13)

Budget Revenues: US$14.03 billion; expenditures:

US$19.69 billion (2013 est.)

Total FDI

US$1.136 bn (2013), US$462.77 m (Jan-June,2013)

Foreign exchange reserves

US$12.35 bn (Nov, 2013)

Currency: Inflation, April,

2013

BDT (1 BDT=US$0.0121) (avg. 2012-13) 7.93per

cent

Exchange Rate Taka (BDT) per US dollar - 81.863 (2014

est.);74.152 (2013 est.)

Industries Jute, cotton, garments, paper, leather,

fertilizer, iron and steel, cement,petroleum

products,tobacco,pharmaceuticals,ceramics,tea

,salt, sugar, edible oils, soap and detergent,

fabricated metal products, electricity and

natural gas Source: Bangladesh Economic Review- Ministry of Finance, March 2014

Bangladesh is becoming increasingly attractive to business and foreign direct

investment. The Foreign Private Investment Act 1980 provides protection to foreign

investors. Bangladesh is a member to the Multilateral Investment Guarantee Agency

(MIGA), Overseas Private Investment Corporation (OPIC), U.S.A.; International Centre

for Settlement of Investment Disputes (ICSID); World Intellectual Property

Organisation (WIPO) and has bilateral agreements to avoid double taxation14

.

14

Board of Investment Bangladesh (2014).

2Table 3.1: Economy of Bangladesh

http://www.mof.gov.bd/en/index.php?option=com_content&view=article&id=72&Itemid=1

http://www.mof.gov.bd/en/index.php?option=com_content&view=article&id=72&Itemid=1

38

3.2.4 Socio-cultural context

After nine months of liberation war ending in 1971, Bangladesh faced severe social,

economic and political problems and took steps to overcome the situation (Sultana

2012). As a result, in recent times there has been remarkable progress in socioeconomic

development indicators for Bangladesh. The United Nations Development Programme

(UNDP, 2013) reported that between the years 1980 to 2012, the Human Development

Index (HDI) rose by 1.5 per cent annually, an increase of 65 per cent overall. The

accelerated growth rate in per capita gross domestic product (GDP) since the early

1990s has impacted on the social development process. Social development indicators

along with per capita GDP ranked Bangladesh among the top performing countries with

similar per capita income level in year 2005 and it is among the few developing

countries achieving targets set by the Millennium Development Goals (World Bank

2005a). According to the UNDP (2010) Report, Bangladesh is making significant

progress in gender equality, primary education, reducing population growth, women’s

empowerment, renewable energy, food production and health. However, political

corruption, political instability, over-population and global climate change continue to

hinder the economic development of the country (Uddin & Suzuki 2011).

Bangladesh encompasses a rich heritage with a remarkable cultural history. Diversity of

social groups in Bangladesh is characterised by an emphasis on social values along with

dominant elite groups (Belal 2001; Parry & Khan 1984). As mentioned earlier, more

than 75 per cent of the population live in rural areas; however, urbanisation has been

occurring rapidly in the last two decades (Bangladesh Bureau of Statistics, 2006). The

largest religion is Islam (about 89 per cent), with the rest of the population following

Hinduism, Buddhism, Christianity and Animists. A high degree of ethnic and religious

harmony exists in the country.

In the late 1990s, the government expanded credit policy and directed banks to sanction

loans to the public sector and give priority to private sector enterprise with low interest

39

rates (Ahmed & Islam 2004). In most cases, public sector loans remain overdue and the

profitability of nationalised commercial banks15

has declined (Ahmed & Islam 2004).

The corporate governance system has been developed following a hybrid of the Anglo-

American outsider-dominated market model (rule and compliance-based) and the

German-Japanese insider dominated bank-based control model (relationship-based)

(Farooque et al. 2007; Islam 2008). However, like many other Asian countries, in

Bangladesh the lack of adequate financial disclosure, weak capital market, corruption,

political instability and an inefficient judicial system impedes establishment of rules and

a compliance-based market (Claessens, Fan & Lang 1999). As a result, the under-

developed institutional settings impact and make a significant difference compared with

developed countries to the socio-economic and cultural context (Ahmed & Islam 2004).

3.2.5 Legal and institutional context

Bangladesh Securities and Exchange Commission

Through enactment of the Securities and Commission Act 1993, the Bangladesh

Securities and Exchange Commission was established as a statutory body under the

Ministry of Finance. The Bangladesh Securities and Exchange Commission acts as the

regulator of the capital market in Bangladesh. By protecting the interests of investors,

along with developing and maintaining a fair and transparent market, the Bangladesh

Securities and Exchange Commission monitors financial institutions, including listed

banks. To encourage high standards of corporate governance, the Bangladesh Securities

and Exchange Commission issued corporate governance guidelines in 200616

. However,

these guidelines do not provide detailed discussion on corporate risk disclosure. Banks

provide their annual financial reports to the Bangladesh Securities and Exchange

Commission, along with their compliance status in relation to corporate governance

guidelines, according to a prescribed form. For non-compliance, with governance

guidelines, the Bangladesh Securities and Exchange Commission prescribes penalties,

with the power to suspend or remove listing privileges.

15

The banking system in Bangladesh is comprised of four State Owned Commercial Banks, four

Specialised Banks, thirty Private Commercial Banks and nine Foreign Commercial Banks. 16

The Code for Corporate Governance for Bangladesh 2006.

40

The Stock Exchanges (Dhaka Stock Exchange and Chittagong Stock Exchange)

After gaining independence in 1971, Bangladesh inherited a single stock exchange, the

Dhaka Stock Exchange that had been established in 1954. The second stock exchange,

Chittagong Stock Exchange, was formed in 1995. Both of these exchanges are regulated

under the Securities and Exchange Ordinance 1969 along with the Companies Act

1994. The major functions of these stock exchanges include listing of companies,

capital market surveillance and monitoring the activities of listed companies. Both

Stock Exchanges place continuous monitoring and reporting obligations on listed

companies in Bangladesh (Akhtaruddin 2005).

The Institute of Chartered Accountants of Bangladesh and the Institute of Cost

and Management Accountants of Bangladesh

The Institute of Chartered Accountants of Bangladesh (ICAB) and the Institute of Cost

and Management Accountants of Bangladesh (ICMAB) are two professional institutions

providing awareness and guidance to the accounting profession in Bangladesh. The

Chartered Accountants Order 1973 and the Cost and Management Accountants

Ordinance, 1977 were responsible for formation of ICAB and ICMAB. These two

statutory organisations are administered through the Ministry of Commerce,

Government Republic of Bangladesh. These two institutions are managed and operated

by internally elected council members.

Initiation of adoption of the International Accounting Standards was started in

Bangladesh in 1999 resulting from a grant from the World Bank. Initially the

Government delegated the adoption process to the Bangladesh Securities and Exchange

Commission. However, due to lack of resources and capabilities, the Bangladesh

Securities and Exchange Commission delegates this responsibility to the ICAB. This

Institute made some minor adjustments and adopted International Financial Reporting

Standards (IFRS) as Bangladesh Financial Reporting Standards (BFRS). ICAB adopted

IFRS 7 as BFRS 7 in January 2010. In more recent times, all BFRS have been updated

based on IFRS 201217

. Although ICAB is responsible for adoption of BFRS, this body

17

http://www.icab.org.bd/index.php?option=com_content&view=article&id=82&Itemid=116

http://www.icab.org.bd/index.php?option=com_content&view=article&id=82&Itemid=116

41

has no legal mandate for enforcement of these standards for listed companies

(Bhattacharjee & Islam 2008; Mir & Rahaman 2005; Sobhani, Amran & Zainuddin

2012). Furthermore, as mentioned in Chapter 2, The Companies Act 1994 and the Bank

Company Act 1991 do not require adherence to any particular accounting standards. As

a result all the risk reporting disclosures in relation to international standards are argued

to be voluntary for Bangladesh banks.

ICAB delivers professional, ethical and technical standards to its members to develop

and support individuals, organisations and communities with sustainable economic

growth. ICAB has global membership with leading accounting bodies across the world

such as the International Federation of Accountants (IFAC), the International

Accounting Standards Committee (IASC) and the Confederation of Asian & Pacific

Accountants (CAPA), the South Asian Federation of Accountants (SAFA), and the

Chartered Accountants of England and Wales (ICAEW).

ICMAB assists in developing, formulating and implementing IFRS and Cost

Accounting and Auditing Standards in Bangladesh. ICMAB members are regarded as

competent cost and management accounting professionals. Like ICAB, ICMAB has

global affiliations, such as with IFAC, CAPA, SAFA, and the IASC.

The Central Bank (Bangladesh Bank)

As a Central Bank, Bangladesh Bank came into existence under the Bangladesh Bank

Order in 1972. As a financial sector regulator in Bangladesh, Bangladesh Bank

regulates and supervises banks and non-bank financial institutions with guidelines,

circulars and directives. Bangladesh Bank guidelines are meant to assist banking

institutions in adopting international best practices and allowing their capital structures

to be more risk absorbent.

In 2010, Bangladesh Bank issued Risk-Based Capital Adequacy guidelines, prepared

based on Basel II and Basel I (Wadood et al. 2010). This guideline was issued with an

aim to establish good governance and managing of risks for banks. The Risk-Based

42

Capital Adequacy guidelines are structured in three aspects; firstly, they outline the

minimum capital requirement for credit, market and operational risks; secondly, they

provide a comprehensive risk assessment process and thirdly, they present a public

disclosure framework for a bank’s risk profile, capital adequacy and risk management

system (BRPD 2010).

According to Bangladesh Bank’s roadmap18

, the year 2010 has been considered as the

full transition to Basel II. However, in practice, only limited number of banks had

adopted by that year (Ahmed & Pandit 2012). According to the Bank Company Act

1991, Bangladesh Bank may impose a penalty for nonconformity if a bank be

unsuccessful to meet minimum capital requirements in the stipulated time, no penalty is

imposed if banks fail to follow other disclosure requirements, such as public disclosure

of banks’ market discipline (Basel II: Market Discipline). After two years, in 2012,

Bangladesh Bank issued another guideline named ‘Risk Management Guidelines for

Banks’19

. This guideline suggested banks submit their quarterly and annual risk

management reports to the board of directors for consideration. However, this guideline

has no suggestion whether this should, in part at least, be included in annual reports. As

a result, banks submit their quarterly report to the Central Bank and do not mandatorily

disclose Basel II: Market discipline disclosures in annual reports.

To strengthen bank supervision, regulatory enforcement and resolution procedures,

Bangladesh Bank adopted a new management structure in 2012 aimed at consolidating

management over onsite and offsite supervision activities (International Monetary Fund

2013). For example, Bangladesh Bank established a ‘Financial Stability Department’ to

assess risks and vulnerabilities in the financial system. Apart from this, the ‘Financial

Integrity and Customer Service Department’ of Bangladesh Bank inspects all banks’

operational risks and their published annual reports, indicating the financial soundness

of each bank.

18

http://www.bb.org.bd/openpdf.php

19




43

3.3 The financial system in Bangladesh

The financial system in Bangladesh is characterised by three major categories; formal;

semi-formal; and informal. The formal category includes all regulated banks and non-

bank financial institutions, insurance companies, capital market intermediaries (i.e.

broker houses, merchant banks) and microfinance institutions. However, semi-formal

institutions (such as non-government organisations, Grameen Bank, cooperatives) are

specialised financial institutions and not regulated under the Central Bank or the

Bangladesh Securities and Exchange Commission20

. The unregulated private

intermediaries comprise the informal sector in Bangladesh.

Figure 3.3 presents the structure of the financial system21

. It can be seen that the formal

categories are comprised of three types of money market; money market instruments are

treasury bills, commercial paper, negotiable certificates of deposits, banker acceptance

and capital market instruments consist of bonds, stock, government securities, bank and

consumer commercial paper, debentures and mortgages. Bangladesh Bank regulates

scheduled, non-scheduled and non-bank financial institutions. As a regulatory body for

the capital market, the Bangladesh Securities and Exchange Commission regulates the

stock exchanges, stock dealers, brokers, merchant banks, and credit rating agencies. The

Insurance Authority and Micro Credit Regulatory Authority regulate 18 life insurance

and 44 non-life insurance companies (as of March 201422

). The Microcredit Regulatory

Authority regulates 599 microfinance institutions (as of March 201423

).

20

Bangladesh Bank Website available at http://www.bangladesh-bank.org/fnansys/index.php 21

The financial system of Bangladesh consists of scheduled and non-scheduled banks, non-bank financial

institutions, microfinance institutions, insurance companies, co-operative banks, credit rating companies,

merchant banks, brokerage houses and stock exchanges. Scheduled Banks are banks that are licensed to

operate under the Bank Company Act, 1991 (Amended in 2003). Non-Scheduled Banks are banks that

are established for special and definite objectives and operate under the Acts enacted for meeting those

objectives. These banks cannot perform all the functions of scheduled banks (Bangladesh Bank 2013a). 22

Bangladesh Bank website available at http://www.bangladesh-bank.org/fnansys/index.php 23

Bangladesh Bank website available at http://www.bangladesh-bank.org/fnansys/index.php

http://www.bangladesh-bank.org/fnansys/index.php



44

Adapted from: Bangladesh Bank website at http://www.bangladeshbank.org/fnansys/index.php

3.4 Banking industry in Bangladesh

The economy of Bangladesh is growing gradually, moving up eight positions in the

Global Competitiveness Index in 2013 (compared to 2008). In addition, per capita

annual income crossed $US1000 recently (World Economic Forum 2013). According to

the ruling Government Mission 2021, Bangladesh wants to be a middle-income country

by 2021 (Bangladesh Bureau of Statistics 2013). The Bangladesh banking sector plays a

vital role in the national economy (Samad 2008; Siddikee, Parvin & Hossain 2013). The

banking sector accounted for 53 per cent of total market capitalisation in June 2013

(Bangladesh Bank 2013b).

9Figure 3.3: Structure of the financial system in Bangladesh

Non-banks

Capital Market

Bangladesh Bank

Formal Informal Semi-Formal

Money Market

Financial Market Regulators and

Institutions

Foreign

Exchange

Market

Banks

Bangladesh Securities and Exchange Commission

Micro credit Regulatory Authority

Specialised

Financial

Institutions

Private

intermediaries

Insurance Authority

Financial system in Bangladesh

http://www.bangladeshbank.org/fnansys/index.php

45

3.4.1 Evolution of the banking industry

The banking system in Bangladesh originated from a Western banking style based on a

mechanism of interest rate spread24

. However, as a member of the Organisation of

Islamic Cooperation (OIC), in Bangladesh Islami Shariah based banks began operations

in 1983. After independence in 1971, the government was committed to rapid

development of the economy after an anarchic situation during the liberation period.

Political independence provided a conducive environment for economic growth in the

newly born Bangladesh. However, most of the private, commercial and service sectors

were owned by West Pakistani entrepreneurs who left the country before or during the

war of liberation time with their properties abandoned (Sobhan & Ahmad 1980). The

newly independent government adopted a socialist model for the economic

development of the country (Sobhan & Ahmad 1980). In line with this policy, the

government nationalised all commercial banks without paying compensation to the

owners of those banks, who were mostly non Bengalis and West Pakistani in identity

(Samad 2008).

After independence, Bangladesh began its journey with six nationalised commercial

banks, two state owned specialised banks and three foreign banks. The existing

commercial banks during the liberation period transferred their assets and liabilities to

the six newly formed nationalised banks. The banking sector was highly controlled and

protected from global competition with nationalised commercial banks in the domestic

market until the mid-1980s. However, financial reform in the banking sector changed

the situation (Sarker 1999).

3.4.2 Structure of the banking sector in Bangladesh

Financial reform in the mid-1980s expanded the banking sector in Bangladesh to

include a number of private banks. The banking system in Bangladesh is comprised of

four State Owned Commercial Banks, four Specialised Banks, thirty Private

24

In banking, the spread is the percentage difference between the interest rate charged on a bank loan and

the lender's cost of funds.

46

Commercial Banks and nine Foreign Commercial Banks. State Owned Commercial

Banks and Specialised Banks are fully or majority owned by government, Private

Commercial Banks are majorly privately owned and listed on a stock exchange and

Foreign Commercial Banks are branches of international banks in Bangladesh

(Bangladesh Bank 2013a). Recently, nine new banks have been permitted to enter the

market of which two are Specialised and seven are Commercial Banks. Private

Commercial Banks are characterised by conventional banking (i.e. interest-based

operations) and non-conventional or Islami Shariah-based (i.e. profit/ loss sharing

mode) banking system. There are seven Islami Shariah-based and three conventional

with Shariah-based25

branches operating in Bangladesh. Evidence from Bangladesh

indicates that Islamic banks can survive within a conventional banking framework by

switching over from a profit and loss sharing mode to trade-related modes of financing

(Sarker 1999).

As of June 2013, 47 scheduled (refer footnote 19) banks were operating in Bangladesh

(Ministry of Finance 2013). The structure of banks with their total number of branches,

deposits and assets is shown in Table 3.2. The Table reports that more than 60 per cent

of total asset deposits are handled by Private Commercial Banks, about 27 per cent of

total assets and 25 per cent of deposits by State Owned Commercial Banks and

Specialised Banks have 5.66 per cent of total assets with 4.91 per cent of deposits.

Source: Annual report, Bangladesh Bank 2014, p.27.

25

Conventional with Shariah-based banking offers both conventional and Shariah products.

3Table 3.2: Structure of the banking system in Bangladesh

(up to June 2013) Type of Banks No. No. of

Branches

Per cent of

Total Assets

Per cent of

Total Deposits

State owned commercial

4 3449 27.17 25.98

Specialised

4 1417 5.66 4.91

Private commercial listed

30 3130 60.82 62.81

Foreign commercial

9 63 6.36 6.31

Total 47 8059 100 100

47

Each of these types of banks has a different pattern of branch location as presented in

Table 3.3. According to the Financial Stability Report (Bangladesh Bank June 2013),

Private Commercial Banks are mostly (i.e. three quarters) located in urban areas.

(Bangladesh Bank 2013b). In addition, 36 per cent of State Owned Commercial Banks

are in urban areas. Specialised Banks are mostly (i.e. three quarters) in rural areas while

Foreign Commercial Banks have no branches in rural areas.

Type of

Banks

No.

of

Banks

No. of Branches Per cent of Total

Urban Rural Total Urban Rural Total

State owned commercial 4 1247 2202 3449 36 64 100

Specialised 4 168 1249 1417 11 88 100

Private commercial 30 1974 1156 3130 63 36 100

Foreign commercial 9 63 0 63 100 0 100

Total 47 3452 4607 8059 42 57 100

Source: Annual report, Bangladesh Bank 2014, p.27.

3.5 Financial reforms in banking sector

To minimise high debt overhang and to increase the stability of the balance of

payments26

, the developing countries around the world experienced major reform in

fiscal adjustment, financial reform, trade liberalisation and privatisation in the 1980s

(Sarker 1999). Bangladesh also entered into financial reform like many other

developing countries with the internal and external pressures that occurred in the mid-

1980s. Internal pressure, such as through the deregulation of the Pubali and Uttara

banks (two of six Nationalised Banks) and external pressure from donor agencies (for

example, the International Monetary Fund (IMF) and World Bank), drove the country to

reform the financial sector (Hossain & Chowdhury 1996). The financial reforms

26

According to Stein (2014), ‘the balance of payments accounts of a country record the payments and

receipts of the residents of the country in their transactions with residents of other countries. See 20th

June,

2014 online at http://www.econlib.org/library/Enc/BalanceofPayments.html.

4Table 3.3: Bank branches in urban and rural areas (up to June 2013)

http://www.econlib.org/library/Enc/BalanceofPayments.html

48

encouraged Private and Foreign Banks to operate with more relaxed policies (Sarker

1999) than previously. As a result, during the 1980s, the loss making State Owned

Banks were privatised, domestic Commercial Banks were promoted and Foreign

Domestic Banks were increased in number (Uddin & Suzuki 2011).

As mentioned earlier, high debt overhang, problems with the balance of payments and

slow growth in many developing countries required financial reform to attain the

objective of financial adjustment, trade liberalisation and to keep control of a

deregulated financial market (Sheng 1996). The developed countries initiated this

reform and South Asian countries followed up the process around the 1980s (Samad

2008). Extant studies evidenced this reform process in several Asian countries;

examples include India (Choudhury 2007), Pakistan (Ahmad & Ahmad 2008), Sri

Lanka (Mukherjee & Nath 2003), and Nepal (Demetriades & Luintel 1996). However,

the outcome of the reform program was mixed (Uddin & Suzuki 2011).

Bangladesh initiated ‘The Financial Sector Reform Programme’ in 1982 with an

objective of encouraging the private sector and to create a competitive capital market

(Samad 2008). During the early phase of reform (in 1984), Bangladesh established ‘The

Money, Banking and Credit Commission’ to define the scope of reform with the

assistance of the World Bank. Under the ‘Financial Sector Reform Programme’,

significant measures were implemented, such as liberalisation in interest rate policy to

improve efficiency, lending and subsidies to priority sectors, improved monetary policy,

strengthening of the capital market, empowerment of the Central Bank, improvement in

State Owned Commercial Banks and reforms in the legal and institutional context.

During the period 1992-1996 the Commission developed new management and

operational tools, such as Lending Risk Analysis, Performance Planning Systems,

Management Information Systems, and the CAMEL (Capital, Asset, Management,

Earnings and Solvency) rating for off-site supervision of banks and disseminated these

tools through an extensive training process to bank officers (Kamal 2006).

The review outcome as evaluated by the ‘Structural Adjustment Participatory Review

Initiative’ in year 2000 indicated that implementation of the reform policy was

49

satisfactory; however, the desired outcome was not achieved (Bhattacharjee & Islam

2008). The Structural Adjustment Participatory Review Initiative Report (2000) further

evidenced that the absence of strict supervision, coupled with rigid economic regulation

by the Central Bank (Bangladesh Bank), could not generate the expected result in the

denationalisation and privatisation process. However, service quality has been improved

rather than overall banking efficiency. The Structural Adjustment Participatory Review

Initiative Committee recommended that macro-economic stability, political

commitment, non-interference by Government and vested interest groups, a

comprehensive framework for demand and supply aspects and sequential policy

measures could assist to achieve the goals of financial reform. The rest of this section

discusses financial reforms in the banking sector.

3.5.1 Risk measure policy reforms in banks

The reform programs aimed to achieve three aspects; policy reform, institutional reform

and legal reform. Bangladesh Bank circulated a number of policy reform frameworks.

The risk-based policy reform, of greatest relevance to this thesis, is discussed in this

section.

Risk based capital adequacy

Capital is the ‘cushion’ that covers the risk of a bank. Capital adequacy is the safeguard

for depositors and describes the financial health of a bank. A Minimum Capital

Adequacy Requirement (MCAR) for credit risks was incorporated in the Bank Company

Act 199127

. With the recommendation of the Bank for International Settlements (BIS),

the Central Bank directed all banks to measure ‘Risk Weighted Capital Adequacy’ in

1996 (Wadood et al. 2010). At that time banks published a summary of Risk Weighted

Capital Adequacy in their annual reports, however, this was not mandatory and Risk

Weighted Capital Adequacy measurement was undertaken primarily for credit risk

measurement. Later, in 2010, to align with international best practices and to make the

27 The Bank Company Act 1991is an act made to make provisions for banking companies

50

capital of a bank more risk sensitive and shock resilient, Bangladesh Bank introduced

guidelines on Risk Based Capital Adequacy for Banks (a revised regulatory capital

framework in line with Basel II). This Guideline recommends banks maintain a

minimum capital requirement, adequate capital, and includes disclosure requirements.

This Guideline assists banks in measuring, assessing and indicating risks appropriately

and follows the Basel II framework in the banking sector of Bangladesh.

Credit Risk Grading

The government’s liberal financial reform policy during the mid-1980s encouraged

banks to reduce interest rates and to increase the volume of credit disbursement in the

financial sector. As a result, National Commercial Banks and Private Commercial

Banks reduced their lending rates. However, the weak association between the bank rate

and the market interest rate in the monetary sector resulted in a decline in the interest

rate spread for Private Commercial Banks and Foreign Commercial Banks

(Bhattacharya & Chowdhury 2003). Under these circumstances, the Bangladesh Bank

introduced a ‘Credit Risk Grading System’ classifying loans into different categories

(BRPD 2009). Bangladesh Bank also published two separate manuals for banks and

non-bank financial institutions (Credit Risk Grading Manual-Banks, Credit Risk

Grading Manual-Non-Bank Financial Institutions).

Classified Loans and Provisioning

Bangladesh Bank has gradually improved the risk assessment process through identifying

early recognition of non-performing loans, resulting in credit discipline and strengthening

the financial stability of banks. At present, the Bangladesh Bank classifies all loans and

advances into four categories, consisting of (a) Continuous Loans, (b) Demand Loans, (c)

Fixed Term Loans, and (d) Short Term Agricultural and Micro Credit (BRPD 2012). If any

doubt arises in recovering loans, the loans are classified under a policy of applying

qualitative judgement into whether loans fall into ‘Sub-standard’, ‘Doubtful’, or ‘Bad Debt’

(BRPD 2012) categories.

51

Interest Rate Deregulation

In 1986, the government appointed ‘National Commission on Money, Banking and

Credit’ to identify major problems and to suggest remedial measures in the financial

system. The Commission recommended that Bangladesh Bank adopt a policy on

interest rate deregulation for both deposit-taking and lending. Bangladesh Bank

circulated this recommendation to all banks and the maximum allowable limit that a

bank can differentiate its rate by is three per cent considering risk elements among

borrowers and the lending category (BRPD 2009).

3.5.2 Institutional reform of risk measures

To improve the institutional capacity of banks in relation to measuring financial

stability and future risks, in the 1990s Bangladesh Bank introduced an off-site

supervision policy, the CAMEL rating. Additionally, institutional reform came through

the Credit Information Bureau and large loan reporting system (Wadood et al. 2010).

Off-site Supervision (CAMELS rating)

The CAMELS rating is a tool used to identify banking companies that have problems

and require increased supervision. Bangladesh introduced the CAMEL rating system in

1993 and a new component ‘S’ (sensitivity to market risks) was added from 2006 to this

rating tool. The CAMELS technique is used to assess the financial soundness and

operating efficiency of a bank and measures the sensitivity of market risks, such as

interest rate risk, commodity prices, equity prices etc. As an off-site supervision project,

Bangladesh Bank uses this device to assess banks’ financial health and to categorise the

bank as a ‘Sound bank’, ‘Early Warning bank’ or ‘Problem bank’ (Bangladesh Bank

2009). The components of the CAMELS rating are:

(C) Capital Adequacy - To strengthen the capital base and to implement the Basel II

accord, the ‘Risk Weighted Asset ratio’ has to be maintained at 10 per cent of which 5

per cent is core capital (Wadood et al. 2010).

52

(A) Asset Quality - Risk is associated with banks’ asset quality (i.e. loans and

advances). Asset quality measures the credit risk associated with particular assets and

identifies the amount and nature of non-performing assets.

(M) Management Soundness - Management competency regarding policies,

procedures, and internal control is judged using different ratios, such as, operating ratio,

profit per employee, expenses per employee, gross earning assets to total assets.

(E) Earnings Ability- Inadequate management may result in loan losses and in return

require higher loan loss allowance or pose a high level of market risks. Earnings ability

reflects the quantity and trend in earnings and factors that may affect the sustainability

of earnings.

(L) Solvency – The fund management practices in banks should be able to maintain a

level of solvency sufficient to meet their financial obligations in a timely manner and be

capable of quickly liquidating assets with minimal loss.

(S) Sensitivity to market risk- Sensitivity to market risks measures the adverse effects

due to deviations in interest rate, commodity price risk, and exchange rate and equity

price risks (Wadood et al. 2010).

Credit Information Bureau

To create a disciplined borrowing environment and to gather information about loan

applicants, the Bangladesh Bank established the Credit Information Bureau in 1992.

The Credit Information Bureau provides credit-related information for existing and

prospective borrowers (Bangladesh Bank 2012a). Bangladesh Bank directs all banks to

obtain a report about loan applicants from the Credit Information Bureau before

sanctioning a fresh loan, renewal of a regular loan, or rescheduling of a loan (BRPD

2009).

53

Large loan reporting system

The Bangladesh Bank established a ‘Department of Banking Operation and

Development’ in 1998 to monitor and review large loans. After examining prospective

borrowers’ applications, this Department allows commercial banks to sanction large

loans and signals the bank concerned to take action against undue risk in relation to

large loans.

3.5.3 Legal reform

The banking industry in Bangladesh experienced expanded regulatory development in

the 1990s. To strengthen the legal infrastructure, the Bank Company Act 1991, Artha

Rin Adalat Act 1990 and Bankruptcy Act 1997, were enacted.

3.6 Motivation for selecting Bangladesh as the context for this study

Bangladesh is selected as the context of this study for several reasons. First, the major

impetus comes from a desire to understand the extent of risk disclosure practices

according to international standards and the underlying factors that determine the level

of risk reporting in the setting of a developing country. As discussed in Chapter 1,

extant corporate risk disclosure studies have been conducted primarily in Western and

European countries. However, developing countries may benefit most from

implementing international standards, as these countries are more economically

vulnerable. The development of global guidance (IFRS 7 [Financial Instruments:

Disclosures] and Basel II: Market Discipline) for corporate risk disclosure thus offers

opportunity to investigate the response to these international standards and examine any

changes in risk reporting in a developing country like Bangladesh.

Second, to date, the risk disclosure literature in the context of developing economies is

scant (Hassan 2009). This study attempts to provide one step towards filling the

research gap by investigating both qualitatively and quantitatively banks’ corporate risk

disclosures and exploring the underlying driving factors for risk reporting by banks in

developing countries.

54

Third, although developing countries are by no means homogenous, they share a

number of political and economic concerns leading to problems in accounting

(Radebaugh & Gray 2005). It is argued that the accounting system in a developing

country should be relevant to the country’s requirements rather than imitating a

developed country’s accounting system (Samuels & Oliga 1982). In addition,

developing economies are characterised by family dominance, corruption and political

interference in corporate governance mechanisms and, therefore, are not conducive to

adoption of Western-styled governance models (Uddin & Choudhury 2008a). Like

many other developing countries, the corporate sector in Bangladesh is characterised by

poor enforcement in the regulatory and monitoring environment with external forces

imposed by donor agencies (Siddiqui 2010). The implementation of international

standards has been motivated largely by the country’s institutional settings along with

its economic, political and social framework. As discussed in Chapter 2, risk disclosure

in financial reporting is effectively voluntary in Bangladesh. Thus, Bangladesh provides

an opportunity to investigate how corporate governance mechanisms and isomorphic

behaviour influence risk governance and risk disclosure in banking institutions.

Fourth, the comparatively large sample of listed banks in Bangladesh, with both

conventional and non-conventional (Islamic) banks also favours selection of

Bangladesh as the setting for this study. As mentioned earlier, the banking system in

Bangladesh embraces both traditional interest rate banking along with a Shariah-based

banking system. Islamic banks in Bangladesh reflect a strong financial position with

future expansion possibilities (Bangladesh Bank 2013b). It is a particularly appropriate

time at which to analyse the extent of risk reporting by non-conventional banks in order

to fill a gap in the literature, as there is a dearth of research examining this sector.

Lastly, as the research seeks to identify risk governance insights and institutional

pressures for risk reporting using both qualitative and quantitative data, the researcher is

able to access for interview key executives at the Central Bank, the Bangladesh

Securities and Exchange Commission and the Commercial Banks, as she is of

Bangladeshi origin. This access assists the researcher to attain the research objectives of

55

this thesis. These aspects make investigating risk reporting in a developing country like

Bangladesh an ideal choice for this study.

3.7 Motivation for selecting listed banks in Bangladesh

The rationale for selecting the listed Private Commercial Banks as the research context

stems from several reasons. First, the economy of Bangladesh continued its rapid

growth and demonstrated considerable resilience during and following the GFC (2007-

2008) period. According to the Bangladesh Bureau of Statistics (2012), Bangladesh

achieved 6.3 per cent in real GDP growth in 2012 (Figure 3.4). The overall growth in

income increased deposits in banks over the period (see Figure 3.5). While the number

of banks has been growing, the amount of deposits has been proportionately increasing

in Private Commercial Banks (Bangladesh Bank 2013b). Therefore, this sector (Private

Commercial Banks) is an attractive context in which to conduct this research.

Source: Financial Stability Report, Bangladesh Bank (2013)

10Figure 3.4: Bangladesh real GDP growth

56

0

1000

2000

3000

4000

5000

6000

2008 2009 2010 2011 2012

Deposits

Deposits

Source: Financial Stability Report, Bangladesh Bank (2013)

Second until 2001, the banking sector in Bangladesh was dominated by Nationalised

Banks, while the growth of Commercial Banks imposed strong competition in the

market with better service quality. The inefficient administrative delay, use of

traditional technology and low regulatory and management supervision increased

interest in Private Commercial Banks. Figure 3.6 shows that around three quarters of

deposits belong to Private Commercial Banks, dominating the sector and growing from

51.4 per cent in 2007 to 60.8 per cent in 2012 while others’ asset share has been

declining (see Figure 3.7).

Source: Annual Report, Bangladesh Bank (2013)

11Figure 3.5: Deposits in years 2008-2012

12Figure 3.6: Deposits in the banking sector, 2012

57

0

10

20

30

40

50

60

70

Pe

rce

nta

ge

Year

SCBs

SBs

PCBs

FCBs

2007 2008 2009 2010 2011 2012

Source: Annual Report, Bangladesh Bank (2013)

Third, the Private Commercial Banks provide their financial data (such as in annual

reports) to the regulatory authorities (Bangladesh Bank and Bangladesh Securities and

Exchange Commission). The unlisted and non-financial sectors are opaque in nature

and provide limited information due to the absence of monitoring.

Finally, as the accessibility of Private Commercial Banks’ annual reports from the stock

exchange, Bangladesh Bank and banks’ websites allows the researcher to acquire

detailed data and to examine the extent of risk reporting practices in Bangladesh. Given

the competitive situation discussed above, the Private Commercial Banks (hereafter-

listed banks) emerge the most suitable sample used in this study.


This Chapter describes the context of financial institutions in Bangladesh in detail. The

financial system, banking evolution, regulatory reforms and the accounting environment

in the country are described in order to explain the contextualisation of the study. The

next Chapter reviews the literature in line with the research objectives of this thesis.

13Figure 3.7: Percentage share of assets (2007-2012)

59

PART TWO

LITERATURE REVIEW AND THEORETICAL UNDERPINNING

Chapter 4: Literature Review

Chapter 5: Theoretical Perspective Underpinning the Research:

Conceptual Framework and Hypotheses

60

Part Two reviews the literature and provides the theoretical perspective underpinning

the research. The discussion in Chapter 4 presents in depth outline of the examination,

explaining the objectives of the research. The Chapter emphasis is on the importance of

disclosure in accounting research, previous related research and outlines the gaps in

previous research. Chapter 5 provides a discussion of theoretical aspects associated with

risk disclosure. That Chapter presents the conceptual framework and hypotheses

developed for the present study also.

61

CHAPTER 4: Literature Review

4.1 Introduction

The objectives of this Chapter to provide a review of financial reporting research

focusing on a specific research area: corporate risk disclosure. The initial discussion

focuses on the meaning of disclosure in accounting research. The Chapter then proceeds

with a review of prior research related to corporate risk disclosure, beginning with a

focus on the banking industry and then moving to non-industry specific studies. A

discussion on the main issue of this broader study follows; that is, ‘risk disclosure

practices: their determinants and performance’, and whether and how existing financial

reporting research addresses this issue. The Chapter leads to a comprehensive

framework of the examination and exposition of the objectives of the study. That is to

identify the extent of corporate risk disclosure practices for all listed banks in

Bangladesh, to identify the association between risk disclosure and determining factors

of such disclosure, and to examine the association of risk disclosure and bank

performance. The structure of this Chapter is presented in Figure 4.1.

14 Figure 4.1: Roadmap of Chapter

Introduction (4.1)

The concept and

classification of

risk (4.2)

The concept of

disclosure in (4.3)

Gaps in the

literature (4.5)

Review of previous

studies (4.4)

Chapter

conclusion (4.6)

62

4.2 The concept and classification of risk

4.2.1 The concept of risk

The present study investigates risk disclosure by banks, thus a principal concern lies in

the definition of risk. In the past, the word risk has been used to reflect adverse events

that have occurred (Deumes & Knechel 2008). However, following the industrial

revolution, the ideas of risks have changed. In the period of Renaissance, the insurance

industry and probability calculations developed the ideas behind risk (Linsley & Shrives

2000). In 1921, Knight introduced the pioneering concept of risk. He explained risk in

economics as a measurable uncertainty. Later on, the term ‘risk’ became used broadly in

everyday language (Linsley, Shrives & Crumpton 2006).

The ‘pre-modern’ idea of risk relates to ‘occurrence of natural events’ (Linsley &

Shrives 2006, p.388). The modern ideas of risk include both ‘positive and negative

outcomes of events’ (Linsley & Shrives 2006, p.388). Extant research defines risk in

several aspects. For example, risk is improbability that take account of either gain or

loss (IASB 2004; ICAEW 1995) and has potential impacts on expected results (Beretta

& Bozzolan 2004). Oliveira, Rodrigues and Craig (2011, p.820) defined risk as ‘actions

taken to manage, mitigate or deal with any opportunity, prospect, hazard, harm, threat,

or exposure’. Dobler (2008, p.187) explains risk using two views- the first view is

‘uncertainty–based…(and) defines risk as the randomness of uncertainty of future

outcome’. The second view is ‘target-based,…(and) defines risk as the ‘potential

deviation from a benchmark or target outcome’ (Dobler 2008, p.187).

According to Solomon et al. (2000) risk may result in either upside or downside risks.

Those authors refer to upside risk as the potential to gain while downside risks are

events where things may go wrong to some extent. Therefore, to create balance, risk

reporting should indicate the range of possible different outcomes with upside and

downside potentials (ICAEW 1999). In the view of the Institute of Chartered

Accountants of England and Wales (1999b), risk disclosure by business should reflect

both opportunities and threats.

63

From a business perspective, risk is influenced by various internal (e.g., finance,

business process, personnel, business strategy) and external factors (e.g., political,

regulatory, market etc.). Dobler (2008) noted ‘corporate risk management continuously

aims at identifying risk factors, analysing and evaluating their potential impact in future

outcomes and addressing the distribution by means of risk handling where appropriate’

(p.187). The key challenge of companies is to identify these risks factors and manage

the possible opportunities they present in a structured way.

4.2.2 Classification of risk

As argued in the earlier section, from an organisational viewpoint, risks arise from

different internal and external sources or factors. Different industries face different

types of risks (Solomon et al. 2000); therefore, it is difficult to establish a complete set

of risk types that are faced commonly by organisations. Different types of risks in extant

literature are defined and summarised in Table 4.1.

Scholars and professional reports have identified risks in several key categories. These

include business risk, political risk and environmental risk (Lajili & Zéghal 2005), non-

financial and financial risks (Cabedo & Miguel Tirado 2004), operational risks,

empowerment risks, information processing and technology risk (Linsley & Shrives

2006), and hazard-based risk (Lenckus 2001). Turnbull et al. (1999) stated risk types as

including business, operational, financial, compliance and other risks. The International

Financial Reporting Standard 7 (Financial Instruments: Disclosures) classifies financial

risk in three types: credit, liquidity and market risk.

It should be noted that the classifications presented in Table 4.1 are not uniform and that

there is no well-accepted classification model or taxonomy of risks. Companies use

different terminology when they refer to risk (Thuélin, Henneron & Touron 2006).

However, for the purposes of this study, the following classification is developed

focusing on risks relevant to banks and dividing risk disclosure into seven categories.

These are: i) Risk Types (Market, Credit, Liquidity, Operational and Equities risks); ii)

Capital Disclosure risks; iii) Internal Corporate Governance risks; iv) Information and

64

Communication risks; v) Strategic Decision risks; vi) General Risks Information; and

vii) Government Regulation risks. These classifications and their coverage are presented

in Chapter 6.

Author and Year Risk Categories

Deumes (2008) Eight risk components including macro environmental sources,

industry sources, internal sources, other sources, loss and

probability of loss, variance, lack of information, and lack of

control.

Papa (2007) Three risk components including environmental risk, process

risk, information for decision-making and eight risk sub-

components (operational, operational decision-making, financial,

empowerment risks, business reporting risk information,

processing risk, integrity risk, and strategic decision-making

risk).

IFRS 7 (2007) Credit, liquidity and market risk (interest, currency and other

price. Other price risks include prepayment, residual value, equity

price, commodity price)

Linsley and Shrives

(2006, p.389)

Financial, operational, empowerment and information processing

and technology risk, integrity and strategic risks.

Lajili and Zegal

(2005)

Financial, political, technology, environmental, weather,

government regulations, seasonality, operational, cyclicality,

suppliers and natural resources.

Cabedo and Tirado

(2004)

Non-financial (i.e. business and strategic); and financial (market,

credit, liquidity, operational and legal)

Institute of Risk

Management (IRM)

(2002)

Risks arise from external drivers and internal drivers, Risk

classified into financial, strategic, operational and hazard.

ICAEW (November

2002)

12 generic categories of risks: accounting, economic and political

environment, financial, human resources, legal/ regulatory/

corporate governance, management information, operation and

markets, project and IT, reputation, strategic, and

terrorist/criminal.

5Table 4.1: Classification of risk in extant literature

65

4.3 The concept of disclosure in accounting and economics

The disclosure-linked research has established into a distinct branch of accounting and

economics area (Frolov 2004). There are researches on disclosure from around the

world covering different aspects in the economics and accounting fields. Several studies

reveal the importance of financial disclosure in improving the accountability of business

entities in different countries (Akhtaruddin 2005; Hossain 2008; Hossain & Hammami

2009; Hossain, Islam & Andrew 2006; Nier & Baumann 2006). Many other scholars

have demonstrated clearly in accounting and economics research the necessity for

financial disclosure (Erkens, Hung & Matos 2012; Michael, Kaouthar & Daniel 2011;

Woods & Linsley 2007).

As expanded upon below, extant studies focus on harmonisation of accounting practices

in the world arena, the extent of disclosure, financial reporting frameworks, financial

reporting disclosure, discovering possible determinants of disclosure, mandatory and

voluntary disclosure association, determinants of regulatory disclosure compliance in

different economies, and non-financial disclosure (such as; corporate social and

environmental disclosure).

Research on corporate risk disclosure practices became widespread in the early 2000s

(see for example, Abraham & Cox 2007; Linsley & Shrives 2000; Linsley & Shrives

2005b; Solomon et al. 2000). An initial study on risk disclosure carried out by Solomon

et al. (2000) found that better risk disclosure would benefit investors in their decision-

making. This study strongly suggested the importance of risk disclosure as a measure of

corporate governance development. Following this study, Beretta and Bozzolan (2004);

Linsley and Shrives (2006); Abraham and Cox (2007); Hashagen, Harman and Conover

(2009); Cornett et al. (2011); Erkens, Hung and Matos (2012) focused more specifically

on risk disclosure in annual reports (the next section discusses these prior studies in

detail).

The GFC of 2007-08 raised the issue of risk disclosure and encouraged regulators and

accounting professionals to develop the quality of financial reporting and enhance its

66

credibility (Erkens, Hung & Matos 2012). The failure of a large number of financial

institutions28

during the GFC (2007-2008) period lead to great public apprehension and

investors becoming gradually doubtful of companies’ annual reports (Hill & Short

2009). Consequently, it has been argued that better communication by companies is

needed to overcome this public distrust and more research is required to guide

management and stakeholders to assess risk and uncertainties of business (Aebi, Sabato

& Schmid 2012; Dobler 2008; Lajili 2009; Woods 2007; Lajili & Zéghal 2005; Linsley

& Shrives 2006).

Hossain (2008) and Verrecchia (2001) distinguished three major disclosure problems in

extant disclosure literature. First, it is vital to determine the economic efficiency of

disclosure; second, it is vital to develop theoretical constructs with hypotheses and third,

it is vital to examine the consequence of disclosure on market performance. The focus

of this current research is on one specific area; corporate risk disclosure practices: their

determinants and the association of risk disclosure with bank performance. For this

purpose, the rest of this Chapter investigates how the existing literature in accounting

addresses the issue of corporate risk disclosure. Consequently, the next section provides

an review of literature on corporate risk disclosure.

4.4 Risk disclosure: Review of previous studies

The combination of concerns about financial reporting on the one aspect and declining

levels of societal trust in large corporations, on the other, continues to provide countless

actions to promote a change in organisations’ business practices (Pearce & Zahra 1992).

In this high scrutiny context, companies are expected to improve not only their

reporting compliance and performance, but are asked also to reveal risk-reporting

information publicly (Solomon et al. 2000). Accordingly, the field of accounting started

to investigate organisations’ disclosure of corporate risk information (Linsley & Shrives

2000). Since the 1990s, the financial accounting literature has been concerned with how

organisations manage their financial activities via disclosure in annual reports and other

28

Bear Stearns, Citigroup, Lehman Brothers, Merrill Lynch (in the U.S.A), HBOS and RBS (in the U.K.),

and Dexia, Fortis, Hypo Real Estate and UBS (in continental Europe) (Erkens, Hung & Matos 2012).

67

reporting mechanisms (Beretta & Bozzolan 2004; Linsley & Shrives 2000; Solomon et

al. 2000).

In past decades, researchers have examined corporate financial disclosure (Amran, Bin

& Mohd 2008; Hill & Short 2009; Hossain 2008; Hossain & Hammami 2009; Kajuter

2006; Linsley & Lawrence 2007; Linsley & Shrives 2000; Linsley & Shrives 2005a, b,

2006; Linsley, Shrives & Crumpton 2006; Schrand & Elliott 1998) and social and

environmental disclosure (Belal 2001; Belal, Cooper & Roberts 2013; Chowdhury

2012; Deloitte 2014; Guerreiro, Rodrigues & Craig 2012; Hossain, Islam & Andrew

2006; Sobhani, Amran & Zainuddin 2012; Villiers & Alexander 2010), amongst other

things. A decade of corporate annual report research (1990-2000) was reviewed by

Stanton and Stanton (2002) and revealed the presence of disclosure studies on image

management, marketing, legitimacy, political economy, accountability and

environmental disclosure; however, none was noted in that review to examine

disclosure of risk information. Similarly, Linsley, Shrives and Crumpton (2006) noted

that in the last 30 years, disclosure studies have focused on corporate disclosure in

general (i.e. financial, environmental, qualitative, quantitative, good/bad disclosure) and

are not specific to risk disclosure. They (Linsley, Shrives and Crumpton [2006]) also

discussed the debate over diversity in risk communication and the usefulness of risk

information to assess the risk profiles of firms.

Previous risk disclosure studies (Abraham & Cox 2007; Amran, Bin & Mohd 2008;

Beretta & Bozzolan 2004; Hernandez-Madrigal, Blanco-Dopico & Aibar-Guzman

2012; Kajuter 2006; Oliveira, Rodrigues & Craig 2011; Solomon et al. 2000) have

focused mainly on companies other than financial institutions. There are also risk

disclosure studies from the perspective of the capital market (Botosan 2004; Healy,

Hutton & Palepu 1999; Verrecchia 2001).

There are some investigations of specific disclosure items (e.g. market risks) in a

specific section (such as the Management Report) of the annual report (Amran, Bin &

Mohd 2008; Michael, Kaouthar & Daniel 2011). These research have investigated the

relationship of risk disclosure with companies’ performance and value and stock price

68

decisions (Aebi, Sabato & Schmid 2012; Amran, Bin & Mohd 2008; Beasley, Clune &

Hermanson 2005; Hoitash, Hoitash & Bedard 2009; Uddin & Hassan 2011). Some

studies examine comprehensively risk disclosure in annual report (Abraham & Cox

2007; Linsley & Shrives 2006; Solomon et al. 2000), while others examine risk

disclosure in prospectuses (Deumes & Knechel 2008; Wallage 2000).

A number of studies have analysed various accounting standards and other documents

and identified the extent of risk reporting in annual reports according to these standards

or other documents (Abraham & Cox 2007; Baysinger & Butler 1985; Eng & Mak

2003; Mair & Marti 2009; PWC 2008; Solomon & Lewis 2002). Apart from these

standards, some studies have concentrated on the richness of information by focusing on

the qualitative nature of risk disclosure (Abraham & Cox 2007; Beretta & Bozzolan

2004; Cabedo & Tirado 2004; Dobler 2008; Lajili & Zéghal 2005; Linsley & Shrives

2006).

Many researchers have investigated the determinants of corporate risk reporting and

found underlying risk reporting determinants, such as size (Beattie, McInnes & Fearnley

2004; Beretta & Bozzolan 2004; Linsley & Shrives 2006). Several studies have

concentrated on past-oriented risk disclosure rather than looking at forward-looking

disclosure (Beattie, McInnes & Fearnley 2004; Kajuter 2006; Lajili & Zéghal 2005;

Mohobbot 2005; Solomon & Lewis 2002). Some studies have focused only on the

management discussion and analysis section (MD &A) in annual reports rather than

investigating the whole report (Beretta & Bozzolan 2004).

Existing studies of corporate risk disclosure can be divided into two streams:

‘academic’ research (Dobler, Lajili & Zéghal 2011 Basel committee 1999, 2000, 2001;

Linsley et. al 2006; Ellul & Yerramilli 2010; Fahlenbrach & Stulz 2011) and ‘audit

firms’ research (e.g. Ernst & Young 2008; KPMG 2008; PricewaterhouseCoopers

2008). The discussion within this Chapter focuses on both streams.

69

4.4.2 Empirical studies of risk reporting by banking institutions

The Basel Committee on Banking Supervision conducted the first risk disclosure in the

context of financial institutions. To achieve the objective of analysing risk disclosure

characteristics, the Basel Committee analysed 54 banks from 13 countries all over world

for a three year (1999-2001) period. The Committee suggested the importance of timely

public disclosure within the context of market discipline (Basel 2003). Basel Committee

papers detailed comprehensive risk disclosure items under 12 categories29

and used a

survey including 104 questions, which were completed by each respective supervisory

authority. However, this study did not provide any further information in relation to risk

reporting in detail except ‘yes’ ‘no’ and ‘not applicable’ responses. The Basel

Committee Report (2003) noticed that increased disclosure over the period pertained to

disclosure of operational, legal, liquidity and interest risks.

One of the first exploratory studies of risk disclosures in the banking sector involved a

comparative analysis between two countries conducted by Linsley, Shrives and

Crumpton (2006). The study uses content analysis of 18 banks (nine British and nine

Canadian), and investigates the nature and characteristics of risk disclosure. They found

a positive association with size, profitability, and extent of risks. A major limitation of

this study is that the authors used qualitative measurement for coding (measured as

good, bad, neutral risk disclosure), which is subjective, at the researchers’ discretion and

depends on an individual’s perception (Amran, Bin & Mohd 2008). Additionally, the

sample size in this study is relatively small in number.

A more specific study was conducted by Helbok and Wagner (2006) who identified

operational risk management as being a fundamental concern for banks. The content

analysis and disclosure index approach used in that study involved examining annual

reports for 1998-2001 of 59 banks from North America, Asia and Europe. This study

concluded that equity and profitability ratios are negatively related to operational risk

29

These include capital structure, capital adequacy, market risk internal modelling, internal and external

rating, credit risk modelling, securitisation activities, credit risk allowances, credit derivatives and other

credit enhancement, derivatives, geographic and business line diversification, accounting policies, and all

other risks.

70

disclosure. However, in general this relationship is expected to be less evident in later

periods due to advances in international standards and risk disclosure regulation.

Additionally this study examined only operational risk disclosure. However, the present

study fills the gap in the literature as this study investigated comprehensive categories

of risk disclosure.

Hossain (2008) examined the extent of both voluntary and mandatory disclosure by

banks in India. The study found profitability, size, board composition and market

discipline variables (non- performing loans, capital adequacy ratio) significant in

explaining the extent of risk disclosure. However, this study used a single year of data

(2002-03) and further research using longitudinal data can measure the changes in risk

disclosure over periods. The present study incorporates longitudinal data to investigate

the development of corporate risk disclosure across the period 2006-2012.

Next, Ismail, Rahman and Ahmad (2013) examined risk disclosure by seventeen Islamic

financial institutions in Malaysia, including banks and non-banks, using data from

2006-2009. They found that risk disclosure had improved greatly over the sample

period. This study is amongst the first to examine risk disclosure in Islamic financial

institutions; however the study did not investigate the determinants of risk disclosure

nor make comparisons with non-Islamic financial institutions. The present study

investigates the determinants of both conventional (Non-Islamic) and non-conventional

(Islamic) banks on a contemporaneous basis over a substantial period.

Apart from the few examples of sector-specific academic research reviewed above,

public accounting firms, such as PricewaterhouseCoopers (PWC), KPMG, and Ernst &

Young have studied corporate risk disclosure. PWC (2008) examined annual reports

from year 2007 using a survey of 22 banks worldwide reporting under International

Financial Reporting Standards (IFRS) or US Generally Accepted Accounting Principles

(GAAP). The results revealed that the quality of risk disclosure had improved compared

to PWC’s previous survey in 2005. However, implementation of the accounting

standards did not result in an immediate improvement in risk disclosure by sample

banks and most samples did not provide a complete depiction of risk disclosure

71

potential best practice (PWC 2008). Another study by Ernst & Young (2008)

investigated the implementation status of IFRS 7 (Financial Instruments: Disclosures)

in 24 of the largest European banks. The key findings suggest that the GFC affected

reporting of risk significantly in year 2007 as banks provided detailed information about

their asset quality (Ernst & Young 2008). These two studies examined whether sample

banks complied with IFRS 7 or not, however, their research methodology was not

explained clearly.

To attain the objective of analysing risk disclosure and related regulation and emerging

ideas in the European financial sector, KPMG (2008) examined the annual reports of 39

European financial institutions (25 banks and 14 insurance companies) for the period

ending 2007. That study identified that risk disclosure in the area of credit risks was

more developed compared to business risk disclosure.

4.4.3 Empirical studies of risk reporting in other than banking institutions

As mentioned in section 4.2, the initial study on risk disclosure was carried out by

Solomon et al. (2000). It suggested the importance of internal corporate governance and

presented a picture of emerging issues surrounding risk disclosure. The authors

developed a conceptual framework for internal control in the context of risk

management and risk disclosure for institutional investors. By conducting a survey of

552 institutional investors in the U.K., Solomon et al. (2000) validates two conceptual

frameworks. This study indicated a need for conducting in-depth case study research of

banks or any other industry in future. The present study includes interviews with

corporate representatives and regulators with an aim to attain insights in relation to

corporate risk disclosure.

Another study by Linsley and Shrives (2000) discussed the merits and demerits of risk

disclosure from business and stakeholders’ aspects. They analysed ICAEW (1998) and

Basel (1998) proposals for greater bank transparency and much-admired the potential

benefits of enhanced risk disclosure. The present study goes beyond those previous

studies by examining the association between risk disclosure and bank performance.

72

Another noteworthy study by Beretta and Bozzolan (2004) contributes to the literature

by providing a multi-dimensional framework for risk analysis of non-financial

companies on the Italian Stock Exchange. The framework is based on risk three aspects

(company characteristics, company strategy, and external environment) and semantic

properties (positive, equal, negative, not disclosed), type of measure (financial/non-

financial, quantitative/qualitative, no measure), and outlook orientation

(information/action) using a sample of 85 non-financial companies. This study paid

attention to specific aspects of ‘what’ and ‘how’ market risk information was disclosed.

The authors found a positive association between the quantity of risk disclosure and size

and no association between the quality of risk disclosure and size. This study has been

criticised, as the quality of information is difficult to measure (Botosan 2004). The risk

disclosure outline in this study deals with many dimensions, which is argued to confuse

readers’ understanding (Thuélin, Henneron & Touron 2006). In addition, that study

examined only the management reports of annual reports. The present study classifies

risk disclosure under seven categories (refer Chapter 6) and the Risk Disclosure Index

used in this research is unique, constructed on international standards and former related

studies.

Classifying risk into financial and non-financial categories, Cabedo and Tirado (2004)

developed a risk quantification model. They used data from 1000 listed non-financial

firms on the Spanish Stock Exchange for 10 years (1991-2001) and calculated the value

at risk (VaR) for sample companies. They classified risks into business, strategic,

market, credit, operational and liquidity risks. However, the results limit the

generalisability of their conclusion for different industries, such as the banking industry.

Another group of studies has examined mandatory and voluntary risk disclosure. For

example, Lajili and Zéghal (2005) examined 300 Canadian Stock Exchange companies.

Using content analysis, this study analysed mandatory and voluntary risk disclosure in

annual reports for year 1999 under 12 risk factors. This study found a high degree of

risk disclosure intensity. However, the authors comment that a lack of uniformity,

clarity and quantification of risk disclosure items could potentially limit their usefulness

(Lajili & Zéghal 2005). Therefore, more formalised and comprehensive risk disclosure

73

is desirable to lessen the asymmetries of information between management and

stakeholders (Lajili & Zéghal 2005).

Several studies examine risk disclosure in non-financial companies. For example,

Mohobbot (2005) examined the relationship between risk disclosure and firm specific

characteristics in Japanese non-financial companies. The study identified that disclosure

of risk is related to company size. Linsley and Shrives (2006) conducted another

significant empirical study. They examined the sample of 79 FTSE 100 annual reports

of non-financial firms for the year 2000. The results showed a positive association

between risk disclosure quantity and firm size. In addition, the companies disclosed a

great amount of forward-looking and good news information in relation to general

statements of risk policy. However, the limitations of forward-looking information are

its incompleteness and it not being useful for investors who usually desire detailed

narrative risk information to understand the risk profile of business. The results also

showed that companies prefer forward-looking disclosure. The findings in this study are

inconsistent with those of Beretta and Bozzolan (2004) and Woods and Reber (2003).

Later, Thuélin, Henneron and Touron (2006) focused on a framework that investigated

listed non-financial companies in France to eliminate the deficiency in the lack of

consensus in laws and regulations of company practice. The study found that there is no

consensus between the different pieces of legislation. However, the study focused only

on mandatory provision of risk disclosure. Another study by Hill and Short (2009)

examined the Unlisted Securities Market and Alternative Investment Market in the U.K

and found that risk disclosure by initial public offering companies contains a greater

proportion of forward looking information rather than internal control and risk

management information.

Narrative risk disclosures from a broader perspective were first examined by Abraham

and Cox (2007). They examined whether the amount of narrative risk disclosure is

associated with ownership, governance and U.S.A. listing characteristics. After

examining 71 FTSE 100 annual reports for the year 2002, the study found risk

disclosure to be negatively associated to shareholders by long-term institutional

74

investors and positively associated to shareholders by short-term institutional investors.

Another finding in this study was that U.K./U.S.A. dual listed firms disclose more

information about risks than single exchange listers. A limitation of this study is that the

authors used words as a recording unit; however, risk related information could be

diluted by using other words. Therefore, the researcher may overlook insights

concerning risk information.

Apart from annual reports, Deumes and Knechel (2008) focused on managers’ financial

motivations for risk disclosure and implementation of sound internal controls over risk

management for public companies from The Netherlands. The study found a positive

relation between corporate risk disclosure and leverage. However, the authors focused

only on sample companies’ prospectuses that predict the volatility of companies’ future

stock price.

Some studies explored the association between risk disclosure and company

characteristics. For example, Hassan (2009) examined 41 UAE listed companies and

explored the association between the extent of risk disclosure and companies’

characteristics. They developed a risk disclosure index by categorising risk into

different groups. However, the index measured the risk disclosure variation among

UAE companies only, as the items were assembled subjectively based on their existence

in the sample companies’ annual reports. Therefore, this index is developed to account

the variation of risk disclosure for the sample country (UAE). However, the Risk

Disclosure Index in the present study is based on international standards and existing

related literatures and not developed for the sample (Bangladesh) country exclusively.

Additionally, Uddin and Hassan (2011) provided evidence on 36 UAE manufacturing

companies and found disclosure of risk information avoided uncertainty and maintained

effective diversification of investment portfolios by investors, which can minimise the

level of market risk. In that study however, it must be noted that the sample size is

relatively small in number.

Taylor, Tower and Neilson (2010) found corporate governance, capital raising, firm size

and leverage to be positively related with the extent of risk disclosure in Australian

75

listed resource firms. However, this study examined only financial risks and was

conducted using data from resource firms.

Marshall and Weetman (2002) first investigated comprehensive corporate risk

disclosure in multi-countries. The study compared regulatory requirements for foreign

exchange risk disclosure in the U.S.A. and U.K. using data from annual reports of 30

(from each country) listed firms. They found disclosure rules implemented in two

countries at the similar period could have dissimilar effects in different governing

settings. The findings lead to the authors’ conclusion that ‘in relation to qualitative

disclosure, there exists a regulatory dialectic in which the opposing forces are the

regulator’s desire for clarity and transparency matched against the corporate

management desire to protect the entity and perhaps to protect the managerial interest’

(Marshall & Weetman 2002, p.48).

Woods and Reber (2003) examined six U.K. and six German companies’ annual reports

for years 2000 and 2001. In particular, this study compared the pattern of risk reporting

between the two countries. The results showed German Accounting Standard 5: (Risk

Reporting) had a positive effect on reporting. However, the extent of risk disclosure is

advanced in the U.K. compared to German companies and the small sample limits

generalised conclusions from this study. Dobler, Lajili and Zéghal (2011) conducted

another multi country study. Using a sample from the U.S.A., Canada, U.K. and

Germany, they found that risk disclosure is published mainly in management reports, is

qualitative in nature, relates to the past and present and is non-time specific.

Recently, Hernandez-Madrigal, Blanco-Dopico and Aibar-Guzman (2012) examined

the impact of the Unified Code of Good Governance on the quality and quantity of risk

disclosure by 35 listed Spanish companies for the period 2004-2009. The authors

conclude that implementation (2006-2009) of the Unified Code has improved the

quality and quantity of risk information (Hernandez-Madrigal, Blanco-Dopico & Aibar-

76

Guzman 2012). However, the study analysed disclosure only in relation to the

Committee of Sponsoring Organisations (COSO) II30

framework.

Another recent study, Probohudono, Tower and Rusmin (2013a) examined voluntary

risk disclosure in South-East Asian countries using a sample of manufacturing firms for

the period 2007-2009 in Indonesia, Malaysia, Singapore, and Australia. Those authors

created a risk disclosure index including 34 items of voluntarily disclosed risk

information. They identified that these countries mostly disclose business risk items

rather than strategy risk. However, the findings limit generalisation to the banking

industry. In another study Probohudono, Tower and Rusmin (2013b) found consistent

risk disclosure during the GFC period. They found that the least developed country (i.e.

Indonesia) has the maximum business risk issues and has inferior level of disclosure

compared to Malaysia, Singapore and Australia. Table 4.2 provides a summary of

empirical research on risk disclosure by banks and non-financial firms.

30

The eight components of the COSO II framework consists of- i) internal environment, ii) objective

setting, iii) event identification, iv) risk assessment, v) risk response, vi) control activities, vii)

information and communication, and viii) monitoring.

77

6Table 4.2: Empirical studies of corporate risk disclosure

Author Focus Explanatory

variables/coding

Research Approach Research Findings Research Gap

Solomon et

al. (2000)

Developed a conceptual

framework refereeing to the

Turnbull Report for internal

control, risk management and

risk disclosure. They focused

on the disclosure aspect of the

conceptual framework for

internal control

Corporate

governance

perception,

investment decision,

demand for

information

Country: U.K.

Data: survey among

552 U.K. institutional

Investors in 1999

Method: Quantitative

(Multiple variable

analysis)

Theory: Agency

Increased risk

disclosure help

institutional investors

in making decision for

their investment

portfolio. In addition,

they require detailed

risk disclosure rather

business risk

information only.

Initial study of risk

disclosure and

indicated a need for

conducting in-depth

case study

Linsley and

Shrives

(2000)

Examine the merits and

demerits of risk disclosure

refereeing to ICAEW proposal

and Basel committee

recommendation on risk

disclosure

Discussion paper Few companies

disclose voluntary

risk disclosure and

argued regulations for

mandatory

requirements.

No empirical

evidence

Marshall

and

Weetman

(2002)

Compared foreign exchange

risk disclosure in between two

countries

Disclosure policy

and information

economics

Country: U.K. and

U.S.A.

Data: 30 Annual

reports from each

country in 1998


Theory: Agency

Disclosure regulations

drawn in two

countries have

different implication

status

Focused only on

foreign exchange risk

disclosure

78


variables/coding


Woods and

Reber (2003)

Compared U.K. and German

companies risk reporting

referring to German

Accounting Standard 5

coding Country: U.K. and

German

Data: 6 Annual

reports from each

country in 2000 and

2001


and Qualitative

(Content analysis)

Theory: not discussed

Observed increased risk

disclosure after post

release of GAS5

through the overall

disclosure is higher in

U.K. compared to

German.

Small sample size

Beretta and

Bozzolan

(2004)

Risk disclosure outline in this

study measure the quality of

risk disclosure

Size, industry Country: Italy

Data: 85 annual

report from non-

financial companies in

2001


Theory: signalling

Size or industry does

not influence quantity

of disclosure.

Quality of disclosure

is difficult to measure

and also many

dimensions of risk

disclosure in this study

confuses the readers’

understanding

Cabedo and

Tirado (2004)

Classified risks in financial and

non-financial category and

established a set of specific risk

quantification model

Risk quantification

model

Country: Spain

Data: 1000 financial

and non-financial

companies from 1991-

2001


(Statistical

Distribution method)

Theory: Agency

Value at risk -

calculated companies’

risks and identified

systematic view of

risks affecting business

activity to put forward

a quantification model.

The results limit the

generalised conclusion

in different industries,

such as banking

Linsley and

Shrives (2005)

Discussion paper on three aspects; first, discussed risk disclosure debate; second, risk disclosure practices, and third, significant issues

arising out of the then proposed Basel requirements.

Mohobbot

(2005)

Examine risk disclosure

practices and firm specific

characteristics.

Size, profitability,

ownership pattern

Country: Japan

Data: 90 non-


Size and risk disclosure

are positively related,

no relationship with

The management

pattern in sample

country is not

79


variables/coding


2003


(Content Analysis-

sentence based

approach)

Theory: Attribution,

institutional

isomorphism

profitability and

ownership pattern

applicable to many

countries.

Linsley and

Shrives

(2006a)

Examined risk disclosure

practices and analysed whether

relationship exists between

company characteristics and

risk disclosure.

size Country: U.K.

Data: 79 non-


2001


(Content Analysis-

sentence based

approach)

Theory: Attribution

theory

Sample country

provides more forward

looking information

rather disclosing useful

information for

stakeholders

Forward looking

information is not

useful for investors

who prefer narrative

risk disclosure

Linsley and

Shrives

(2006b)

Examined nature and practices

of risk disclosure practices in

banking institution.

size, risk level, and

quantity of risk

Country: U.K. and

Canada

Data: 9 banks from

U.K. and Canada in

2001


(Content Analysis)

Theory: Agency,

signalling, legitimacy

Little quantitative and

past risk information

limit the usefulness of

disclosure

Small sample size and

difficult to measure

quality of risk

disclosure

80


variables/coding


Thuélin,

Henneron and

Touron (2006)

Focus on mandatory risk

reporting applying to

companies leads to the question

of whether or how companies

are compliant with regulations.

Coding

Country: France

Data: Annual

Reports, laws,

accounting standards,

professional source

Method: Qualitative

(Interactive model)

Theory: Grounded

Laws and regulations

terminology differ in

different countries.

Focused only on

mandatory risk

disclosure

Helbok and

Wagner

(2006)

Referring to the Basel

Committee Report, the study

focused on operational risk

disclosure

Equity, profitability Country: From North

America, Asia and

Europe

Data: 59 banks from

1998-2001


(Content Analysis-

word count)

Theory: Agency ,

signalling and

political cost

Equity and profitability

ratio is negatively

related to operational

risk disclosure

Only operational risk

is examined

Linsley and

Lawrence

(2007)

Focus on readability and

obfuscation of risk disclosure

Readability, good

news, bad news

Country: U.K.

Data: 25 largest non-

financial companies

annual reports in 2001


(Content Analysis-

sentence based

approach using Flesch

Reading Ease

formula)

Theory: Attribution

Level of readability of

risk disclosure is

difficult

Overlooked the

understandability of

disclosure

81


variables/coding


Abraham and Cox

(2007)

Referring to FRS 13

and the Turnbull

Report examines the

quantity of risk

information

Ownership governance

and U.S.A. listing

characteristics

Country: U.K.

Data: 71 annual

reports in 2002


(Content Analysis-

word based approach)

Theory: Agency

Risk disclosure is

negatively related to

share ownership.

Uses words as a

recording unit,

however, companies

can dilute risk related

information using

other words.

Furthermore, this study

only analysed the

narrative content of

annual reports.

PWC (2008) Referring to IFRS and GAAP the study surveyed 22 banks world-wide to examine whether the

sample banks implement fair value, structure finance and risk management and found the standards

positively influence reporting however, most of the banks did not provide a complete depiction of

risk management practices.

Survey study.

Methodology was not

clearly explained.

Ernst Young (2008) The study investigated the implementation status of IFRS for 24 largest European banks. The key

finding of this study is that after the recession, banks’ financial reports are more detailed.

KPMG (2008) Examined 39 European Financial institutions (25 banks and 14 Insurance companies) for the period

ending 2007 and identified the risk disclosure area in credit risks are the most developed compared

to business risks disclosure.

82


variables/coding


Hossain (2008) Investigated the extent

of disclosure and the

relation between

company

characteristics

Age, size, profitability,

complexity of

business, assets in

place, board

composition, market

discipline

Country: India

Data: 38 banks in

2003


(Multiple variable

analysis)

Theory: Agency

Regulatory monitoring

brings the sample

banks in compliance of

mandatory disclosure

Only single year data

was analysed

Deumes (2008) Examines managers

financial motivations

for risk disclosure, and

governance

Ownership

concentration,

managerial ownership

and financial leverage

Country: The

Netherlands

Data: 490 companies

from 1997-1997


(content analysis,

regression, logit and

probit analysis)

Theory: Signalling

Risk section in

prospectuses predicts

volatility of

companies’ future

stock price

The study could not

differentiate between

private debt and public

debt; therefore the

internal control

disclosure demand

may differ between

these two

Hill and Short (2009) Examines the risk

warning disclosure of

initial public offering

(IPO) companies and

underlying factors

Information

asymmetry,

monitoring,

proprietary costs, and

nominated advisor

reputation capital

Country: U.K.

Data: 420 IPO

companies on the

Unlisted Securities

Market (USM) and

Alternative Investment

Market (AIM) in

1991-2003


(content analysis,

regression, logit and

probit analysis)

Theory: Signalling

IPO companies’ risk

disclosure is forward

looking rather than

disclosing internal

control and risk

management

information

The concluding

remarks may not be

generalisable for listed

banks or financial

institutions

83


variables/coding


Hassan (2009) Developing a Risk

Disclosure Index, the

study explored the

relationship among the

level of risk disclosure

and companies’

features.

Size, level of risks,

industry type

Country: UAE

Data: 49 financial and

nonfinancial

companies in year

2005


(Multiple regression

analysis)

Theory: Institutional

Size is not

significantly related

with extent of risk

disclosure whereas

industry type is

significant in

explaining risk

disclosure

The index items are

subjectively assembled

based on sample

companies.

Taylor et al. (2010) Examines financial

risk management

disclosure

Adoption of IFRS,

corporate governance,

capital raising and

jurisdiction

Country: Australia

Data: 111 extractive

resource companies

2002-2006


(Ordinary Least

Square regression)

Theory: Agency

IFRS has positive

impact on reporting

Resource firms and

financial risk were

analysed.

Dobler, Lajili, Zeghal

(2011)

Focused on multi

country risk disclosure

in manufacturing

companies

Size, country Country: U.S.A.

Canada, U.K. German

Data: 160 companies

in 2005



analysis)

Theory: Agency

Size positively affects

number of risk

disclosure and negative

association between

leverage and quantity

of risk disclosure in

Germany. Positive

association in North

American settings.

Number of disclosure

cannot capture the

weights of information.

Cross-country findings

are not generalisable.

84


variables/coding


Uddin and Hassan

(2011)

Examines whether

more risk disclosure

has a negative

association with stock

price and market risks.

Corporate risk

disclosure, Volatility

of securities return,

market risk factor

Country: UAE

Data: 36 companies in

2005



analysis)

Theory: Capital asset

pricing, portfolio

theory

Risk disclosure has no

negative association

with the variables

examined

Only single year data

was analysed

Hernadez-Madrigal,

Blanco-Dopico and

Aibar-Guzman (2012)

Referring to COSO,

the study examines the

impact of Unified

Code of Good

Governance on the

quality and quantity of

corporate risk

disclosure

Coding Country: Spain

Data: 35 listed

companies from 2005-

2009


(Content Analysis-

word count)

Theory: Legitimacy

The code influences

positively risk

disclosure narratives

COSO framework is

not adequate for

financial institution

analysis.

Probohundono, Tower

and Rusmin (2013)

Examined voluntary

risk disclosure of

South-East Asian

Countries

Country;

company size;

managerial ownership;

and board

independence.

Country: Indonesia,

Malaysia, Singapore,

and Australia

Data: 15

manufacturing

companies from each

country for 2007-2009



Analysis)

Theory: Agency

Positive association

with Country, size

and board

independence and

negative association

with leverage and risk

disclosure

Small sample size

85


variables/coding


Ismail, Rahman and

Ahmad (2013)

Examine risk

disclosure in Islamic

financial institutions in

pre and post-recession

periods

Scored risk disclosure

index

Country: Malaysia

Data: 17 Islamic

financial institutions

from 2006-2009



Analysis)

Theory: Not discussed

The disclosure in

Islamic financial

institutions has been

improved across the

period

They did not

investigate the reason

for the increased level

of risk disclosure.

86

4.5 Gaps in the literature

This Chapter discusses financial reporting research with a particular focus on corporate

risk disclosure. Prior research on corporate risk disclosure has attempted to provide an

understanding of the trends in and motives for this type of disclosure. A review of prior

research on corporate risk disclosure practices recommends that the incidence and

quality of corporate risk disclosure practices has increased substantially since the 1990s

in general and the GFC (2007-2008) in particular. However, much of this literature

relates to developed countries. The discussions in this Chapter give directions to

consideration of the following research lacks in the relevant literature:

1. A review of prior literature indicates that currently there is a lack of research

investigating risk disclosure practices. While the extant research on risk disclosure

focuses primarily on the extent of risk disclosure practices based on annual reports, no

research to date has examined banks’ disclosure practices in relation to the international

standards banks have in place for addressing various issues associated with risk

disclosure. The in-depth interviews with banking regulatory representatives in this study

aim to attain insights to such disclosure.

2. A review of the literature also highlights that no research to date has documented a

longitudinal study that investigates banks in an emerging country (such as Bangladesh)

within their corporate governance context. Bangladesh it is argued is a site where

adoption of international standards, even by listed banks, is effectively voluntary. The

study of this nature would provide meaningless results if it was conducted using data

from a high rule of law country where enforcement of governance, accounting and

prudential standards is mandated (Chapters 2 and 3 explain in detail the necessity for

this context). Additionally, a longitudinal study could provide insights to risk reporting

practices.

3. A review of the literature also highlights that no research to date has documented risk

disclosure practices and determinants of risk disclosure within financial institutions.

87

The above deficiencies lead to the value of this particular research, which attempts to

add to the existing body of knowledge in investigating the nature of risk disclosure by

banks in Bangladesh. This study also seeks to explore the underlying factors that

explain risk disclosure and performance.


The aim of this Chapter was to find out whether and how the extant accounting

literature addresses a specific financial reporting issue- in particular, risk disclosure

practices. A review of the literature points to gaps in extant financial accounting

research dealing with risk disclosure, many of which this study seeks to overcome.

While investigating the research issues identified in this Chapter, it is important to

embrace the relevant theoretical framework underpinning the research. In this regard,

Chapter 5 provides a thorough discussion of underpinning theories, as they are

appropriate to attain an understanding of the research objectives of this thesis.

89

CHAPTER 5: Theoretical Perspective Underpinning the Research -

Conceptual Framework and Hypotheses

5.1 Introduction

The aim of the study involves three interrelated aspects. The first aim is to investigate

the extent of risk reporting practices by listed banks in Bangladesh. What risk

information is disclosed in relation to best practice suggested by international standards

is investigated. The second aim is to explore the underlying factors associated with risk

reporting in relation to bank characteristics. Previous studies evidenced a variety of

theoretical perspectives to explain the determinants of disclosure. This study however,

restricts attention to agency theory to justify the hypothesised corporate governance

factors and neo-institutional theory to explain the hypothesised external isomorphic

influences on risk disclosure. The third aim of this study is to examine whether risk

disclosure has an association with bank performance.

The timeline for this present study lends to its importance, coming as it does a few years

after the publication and implementation of IFRS 7 and its amendments and BASEL II:

Market Discipline. In the Bangladesh context, it is expected that risk disclosure would

be increased as an evidence of and endorsement towards corporate governance

improvements (Solomon et al. 2000). This research hypothesises that banks will

respond to these international standards by enhancing the extent of risk disclosure even

where compliance is not compulsory as in a country such as Bangladesh. This leads to

the first hypothesis:

H1: There are significant differences in risk disclosure over the period under

examination (2006-2012).

The objective of this Chapter is to provide a discussion of theoretical aspects associated

with corporate risk disclosure, an important initial step in developing the conceptual

framework and Hypotheses for the present study. Theoretical considerations assist in

explaining the phenomenon of risk disclosure and managers’ motivations in disclosing

voluntary disclosure in addition to that required by legislation. The Chapter commences

with discussion of underpinning theories followed by development of research

hypotheses . Figure 5.1 provides an overview of this Chapter.

90

5.2 Theories discussed in previous disclosure studies

Prior literature on disclosure has focused mainly on institutional theory (Hassan 2009),

stakeholder theory (Amran, Bin & Mohd 2008), signalling theory (Helbok & Wagner

2006; Linsley & Shrives 2000; Marshall & Weetman 2002), agency theory (Abraham &

Cox 2007; Aziz A 2009; Bertomeu, Beyer & Dye 2011; Deumes & Knechel 2008;

Helbok & Wagner 2006; Lajili 2009; Linsley & Shrives 2000; Oliveira, Rodrigues &

Craig 2011), legitimacy theory (Oliveira, Rodrigues & Craig 2011), political cost theory

(Helbok & Wagner 2006; Linsley & Shrives 2000), capital need theory (Choi 1973),

and proprietary theory (Kajuter 2006; Mohobbot 2005). However, no single theory has

been available that articulates the phenomena of disclosure completely (Linsley &

Shrives 2000).

This study extends the analysis of risk disclosure practices and examination of

determinants of risk disclosure based on agency theory and neo institutional

isomorphism. The following section discusses the relevance of these underpinning

theories in detail.

5.3 Agency theory

Agency theory has dominated in the literature on economics and accounting and finance

(Hermalin & Weisbach 2012). The key idea of this theory is that the principal-agent

relationship should use information in the organisation efficiently to minimise

information asymmetry and risk bearing costs (Eisenhardt 1989). The shareholders act


Introduction (5.1)

Theoretical

perspective of

previous studies (5.2)

Agency theory (5.3)

Conceptual

framework (5.6)

Chapter conclusion

(5.7)

The relation between

risk disclosure and

bank performance

(5.5)

Institutional theory

(5.4)

91

as principals and managers as agents under this theory. Jensen and Meckling (1976,

p.308) define the agency relationship as ‘a contract under which one or more persons

(the principal(s)) engage another person (the agent) to perform some service on their

behalf which involves delegating some decision-making authority to the agent’.

Eisenhardt (1989, p.59) outlined two aspects of agency theory- the ‘principal-agent’

stream and ‘positivist’ stream. The principal-agent stream has a broader focus than the

positivist stream and greater interest in general in pointing out effective contracting

alternatives. The principal-agent relationship can be functional in any agency

relationship, such as employer-employee, lawyer-client, buyer-supplier. However, the

positivist stream focuses on classifying situation where agency relationship have

conflicts to accomplish their objectives and then describes the governance

mechanism(s) that control agents’ self-interested behaviour (Eisenhardt 1989).

Despite its wide scale use in several disciplines, including the accounting area, agency

theory has encountered controversy and has its critics. Perrow (1986) cited in

Eisenhardt (1989, p.58) argues that agency theory is ‘hardly subject to empirical tests

since it rarely tries to explain actual events’. Further to that, agency theory is one-sided

and fails to explore other key issues such as exploitation of workers (Eisenhardt 1989).

Moreover, the inherent distrust in agency theory perspective leads to a dehumanisation

of the agent, where the intrinsic motivations are ruthlessly replaced with a rational

calculation of the value of consequences (Shapiro 2005; Surendra 2010). Therefore, the

agency theory perspective is purely made for a model to be workable mathematically

and reduce agents’ dynamism (Ghoshal 2005; Surendara 2010). This has been

complemented by the development of a system based on formal rules, norms and moral

principles previously found in a rational society (Coleman 1993).

5.3.1 The agency problem

Shareholders delegate authority and responsibilities to the board of directors. As a

result, agency theory conceives two potential problems that may arise within the

manager-shareholder relationship: moral hazard and adverse selection.

92

In the context of agency relationships, a problem of information asymmetry occurs as

the agents have an information advantage. Shareholders may have limited ability to

assess managerial decisions. Consequently, managers may take advantage of greater

information access to increase their individual wealth (Foerster , Sapp & Shi 2013).

Information asymmetry creates moral hazard issues and may lead to imprudent

decisions from shareholders’ perspective. Jensen and Meckling (1976) hypothesised

that if principals and agents seek to maximise their own self-interest, agents become

opportunistic and maximise their own welfare by serving their own best interest. As a

result, they do not pursue maximisation of principals’ wealth. However, using a

monitoring system through financial disclosure may assist to lessen the agency problem

(Miller & Noulas 1996).

Adverse selection arises as a consequence of misrepresentation of the agent’s abilities.

Without the appropriate skills and abilities, the agent takes wrong decisions in respect

of the organisation’s policies and disclosure decisions.

Jensen and Meckling (1976) identified two classes of agency conflict: these involve

compensation contracts and owner-debt holder contracts. They further suggested that

accounting reports and disclosure of information could decrease the costs of these

conflicts, increase shareholders’ confidence level and reduce information asymmetry.

Figure 5.2 depicts the agency relationship between principals (shareholders) and agents

(managers) which can be let down by conflict.

Figure 5.2 shows the agency problem and scope of monitoring arising through

governance mechanisms. Contracts reduce the misalignment of interests. However, in

complex business environments, contracts cannot cover all eventualities. When

contracts fail to achieve their desired objectives, the principal relies on governance

mechanisms to supervise the agent.

93

Source: Cullen, Kirwan and Brenan (2006, p.11)

Further, Fama and Jensen (1983) argued that an agency problem arises as there is a

conflict of interest concerning principals and agents in relation to agency costs, such as,

costs of organisational structuring, monitoring, and bonding where contracts are not

written or, where written are not enforced. Effective supervisory practice can lessen

agency problems (Fama & Jensen 1983).

5.3.2 Agency theory and the organisational perspective: Association of

agency theory with disclosure

Eisenhardt (1989) identified that agency theory contributes to organisational thinking in

two aspects. The first is the usage of information that plays a vital role in the formal

information system, such as budgeting and more informal aspects such as managerial

supervision. A rich information system provides control over managerial opportunism.

Agency theory suggests the board can be used for monitoring purposes in shareholders’

16Figure 5.2: Agency theoretical perspective

Principal Agent Agency

relationship

Agency problem/conflict

Contract

Imperfect

contract

Perfect contract

Agency

costs

Governance

Mechanisms

Residual

agency costs

Bonding Costs

94

interests (Fama and Jensen 1983). Second, another contribution of agency theory is in

its risk implications as an uncertain future is controlled in part by organisation

members, rather than being influenced by governmental regulations, emergence of new

competitors or rapid technological innovation. Several empirical studies, such as

Botosan (2004); Healy, Hutton and Palepu (1999) have found a negative association

between the cost of capital and disclosure of information. The cost of equity capital

decreases when the amount of disclosure increases (Botosan 1997). In addition, a high

level of disclosure can increase market solvency, which leads to a more efficient capital

market by avoiding potential market failure (Healy, Hutton & Palepu 1999).

As stakeholders need to understand the risk profile of businesses, they seek information

about the risk profile to be disclosed by companies, together with how risks are being

managed. Improved risk disclosure assists stakeholders to be more aware of internal

governance and to interpret the level of various risks the company faces. These higher

levels of transparency simplify interpreting risks for external users and reduce agency

costs (Cabedo & Miguel Tirado 2004; Hill & Short 2009; Marshall & Weetman 2002).

In addition, operational risk disclosure might have the potential to reduce the cost of

capital, agency costs, and the cost of financial distress (Helbok & Wagner 2006).

Solomon et al. (2000) argue that risk disclosure represents a means of controlling the

agency problem. Furthermore, risk disclosure and sound governance are of interest to

regulators as they reduce agency problems (Abraham & Cox 2007).

Agency theory presumes that the board of directors will exercise the primary control

function in business organisations. Corporate governance mechanisms serve to monitor,

discipline, and remove ineffective management teams to ensure that managers pursue

shareholders’ interests (Ben Naceur & Kandil 2009). Therefore, functional governance

mechanisms with positive attributes (such as board independence, audit committee

independence, the presence of a risk committee) are necessary. In summary, agency

theory principles are advanced as an underpinning theoretical justification for the

development of Hypotheses in this study. The following section discusses these

Hypotheses in detail.

95

5.3.3 Relevance of agency theory in this study: Development of Hypotheses

This study focuses, in part, on agency theory in achieving its research objectives.

Agency theory is relevant to this study as it describes that information asymmetry

between principals and agent can be decreased by supervising the opportunistic

behaviours of agents (Jensen & Meckling 1976). Annual report disclosures provide a

mechanism for reducing monitoring costs and assist to lessen agency problems (e.g.

moral hazard and adverse selection). Moreover, in an active capital market, financial

reporting disclosure reduces information asymmetry and hence lessens the monitoring

burden between principals and agents (Marshall & Weetman 2002). Managers are

expected to have incentives to disclosure; for example, to keep their reputation and

remuneration (Healy, Hutton & Palepu 1999). Disclosure can mitigate information

asymmetry problems (Botosan 1997; Hill & Short 2009). If managers choose not to

disclose relevant information in annual reports, the information gap results in less

transparency in the annual report (Marshall & Weetman 2002) and the withheld

disclosure consequence is a possible conflict of interest concerning principal and agent.

This information may also affect users’ perceptions.

Unlike many other developing countries, in Bangladesh the corporate sector faces weak

enforcement of international standards (International Monetary Fund, World Bank) along

with poor legal structure (Khan, Muttakin & Siddiqui 2013). However, corporate

accountability, governance and transparency are vital for the development of and

sustainable growth in any country (Abhayawasnsa & Azim 2014). Shareholders and

creditors tend to introduce monitoring mechanisms to observe risk management

activities (Linsmeier et al. 2002). However, nonexistence of monitoring systems,

managers may be opportunistic in manipulating or providing misleading disclosure

(Latham & Jacobs 2000). Monitoring mechanisms depend on having an independent

board (Abraham & Cox 2007; Deumes & Knechel 2008; Lajili 2009; Oliveira,

Rodrigues & Craig 2011); an independent audit committee (Fraser & Henry 2007;

Oliveira, Rodrigues & Craig 2011); and risk committee (Aebi, Sabato & Schmid 2012).

96

Board Independence

Independent directors are defined as directors who do not have any other relationship,

whether pecuniary or otherwise, except for their board seat, whereas directors with any

other business ties are known as non-independent (or ‘grey’) directors (Aebi, Sabato &

Schmid 2012). It is expected that independent directors are impartial in disclosing more

risk information than non-independent directors disclose. The GFC of 2007-2008 has

been used as a setting in which to examine the performance of independent directors on

boards in several studies (Adams 2012; Beltratti & Stulz 2012; Hermalin & Weisbach

2012). Theoretically, independent directors have little involvement in daily internal

business and are not influenced by corporate insiders (Lim, Matolscsy & Chow 2007).

They are motivated to demand more risk disclosure than executive directors do to

balance the level of risk in the business and thereby maintain their personal reputations

(Amran, Bin & Mohd 2008; Beasley, Clune & Hermanson 2005; Oliveira, Rodrigues &

Craig 2011).

Consistent with previous studies, this study follows agency theory and adopts

independent board as a risk governance factor in explaining the level of risk disclosure.

The next Hypothesis is:

H2: The number of independent directors on the board is associated positively

with the extent of risk disclosure

Audit Committee Independence

Banks with a higher percentage of independent directors on the audit committee are

more expected to monitor the internal control risk management and risk reporting

process effectively (Fraser & Henry 2007; Oliveira, Rodrigues & Craig 2011). Boards

require support from audit committees to assist in ensuring transparency and

accountability and to monitor diversified business operations by reducing agency costs

(Fraser & Henry 2007). Independent directors on the audit committee assist in ensuring

the effectiveness and reliability of audit committees (Turley & Zaman 2004). The

Hypothesis is:

97

H3: The number of independent directors on the audit committee is associated

positively with the extent of risk disclosure.

Risk Committees

Risk committees assist in ensuring that a wide range of risks in banks is identified and

that risk exposures are managed within the risk strategy. By helping to maintain risks at

a desired level, risk committees assist in achieving banks’ desired financial goals. The

various types of risk committees include ‘asset/liability management committees, credit

committees, purchase committees, bank operation risk committees and bank risk

management committees. After the GFC (2007-2008), banks devoted greater attention

to risk disclosure and increased the number of risk committees and segregated their

duties and responsibilities (Aebi, Sabato & Schmid 2012). Therefore, it is expected that

the more a bank acknowledges its risk reporting concerns through establishing more

effective risk committees, the more likely it is to provide risk disclosure in its annual

report. However, given that data proxies for risk committee effectiveness (such as,

number of meetings, independence of members etc.) is not likely to be disclosed for

many banks in the sample, the number of risk committees is used as a proxy. Risk

committees monitor risk exposure, policies and procedures affecting loans, non-

performing loans, market, and operational areas within the risk strategy and risk appetite

of the bank, as established by the board of directors. Therefore, the following

Hypothesis is proposed:

H4: The number of risk committees is positively associated with the extent of

risk disclosure.

5.4 Institutional theory

Institutional theory takes a predominantly sociological view of organisations’

operational practices (Ahmed & Pandit 2012; Bank 2012b; Basel 2001). It is concerned

with ‘the relationship between organisations and their environments’ (Powell &

DiMaggio 1991 p.12). Institutional theory asserts that the process of creation of an

institutional environment, such as through rules, norms, structures and schemes,

influences entities strongly to form authoritative guidelines and develop formal

organisational structures (DiMaggio & Powell 1983; Scott 2004). Social and

institutional pressures impact organisational practices and procedures to be empowered

to prevail in social expectations to gain, maintain and repair legitimacy (Lenckus 2001).

98

The initial literature on institutional theory is now considered ‘old institutional theory’

and was developed by Berger (2011); Beyer et al. (2010). At that time, institutional

theory considered the organisation as an ‘adaptive organism’ embedded in a local

community environment and responding to pressure from the external environment,

depending on the organisations’ leadership and employees’ commitment.

Institutionalisation provides value to the structure (Beyer et al. 2010), and promotes

stability so that the structure persists over time (Farooque et al. 2007) to achieve

organisational effectiveness.

‘New institutional theory’ added a new outlook to the old institutional theorists, viewing

‘environment’ and ‘institution’ from a wider perspective in relation to professional and

industrial aspects. The new institutional theory31

is based on the concept of the social

structure of reality introduced by Shapiro (2005). New institutional theorists argue that

an organisation is embedded by behaviour and practices in order to be legitimate in its

environment and highlight the symbolic value of institutionalisation (DiMaggio &

Powell 1983; Laux & Leuz 2009). Therefore, ‘organisations require more than material

resources and technical information to survive and thrive in… (the environment). They

also need social acceptability and credibility’ with material and technical information

(Basel 2001, p.237).

To achieve societal justification and trustworthiness, institutional rules, norms, structure

and procedure function as powerful myths (Laux & Leuz 2009) that firms implement.

Laux and Leuz (2009) argued that ‘institutionalization involves the processes by which

social process, obligations, or actualities come to take on a rule-like status in social

thought and action’ (p. 341). In order to define institutional theory for the present

research, it is essential to define the meaning of ‘institution’ in the accounting literature.

5.4.1 Defining institution

31

New institutional theory is also termed as neo-institutional theory, new institutionalism and neo-

institutionalism.

99

The term ‘institution’ is used widely with different conceptualisations (Hollingsworth

2003). North (1990) proposes the commonly accepted definition of institutions as the

‘humanly devised constraints that shape human interaction’ (p.3) providing the ‘rules of

game in society’ (p.3)32

. According to Basel (2001, p.48), institutions are ‘social

structures that have achieved a high degree of resilience’. Basel (2001) describes

institutions as consisting of three elements; first, regulative which is comprised of laws

and regulation and the environment and coerces organisations to be legitimate; second,

normative includes norms and values that are developed in the institutional

environment; and third, cultural-cognitive elements shared by society and carried by

individuals. All of these factors together establish the rules of organisation.

Wysocki (2011) asserts that the actions of players (organisations) are governed by rules

(institutions). The rules are the combination of skill, strategy and coordination to win

the game, reduce uncertainty and determine the organisation’s success over time (North

1990). The definition includes political bodies (for example, political parties and

regulatory agencies), economic bodies (for example, firms, trade unions and

cooperatives), social bodies (for example, clubs and social associations) and educational

bodies (such as schools, universities and training centres), bound together to achieve

certain objectives. DiMaggio and Powell (1983) argued that organisations implement

structures that are legitimate, socially acceptable or imperative to achieve organisational

efficiency.

There are five basic elements that build the framework for ‘new institutional

accounting’ research that analyses the determinants and outcomes of accounting

institutions and non-accounting institutions (Wysocki 2011). These are, firstly,

institutional structure (formal versus informal). Informal institutions include values and

social norms whereas formal institutions are formed with laws and regulations (North

1990; Scott 2008). However, formal and informal institutions can be mutually

reinforcing because values and norms are often formalised into laws and regulations

while laws and regulations can provide validation of values and norms (Wysocki 2011).

Secondly, the level of analysis differentiates macro-institutions from micro-institutions.

32

Douglass C. North, the Alfred Nobel Memorial Prize winner in Economic Sciences (1994).

100

Thirdly, is causation that includes ‘exogenous’ and ‘endogenous’ institutions.

Exogenous institutions are the macro-level rules for both formal and informal

institutions, including the legal system, cultural norms and social patterns. Endogenous

institutions are micro-level rules for formal and informal institutions (Davis & North

1971). Fourthly, is interdependencies and fifth and finally, efficient versus inefficient

outcomes.

A multi-level institutional analysis is developed by Hollingsworth (2003) which can

assist in positioning of research. This analysis is reproduced in Table 5.1 The present

study is within the scope of the third level of Hollingsworth’s (2003) analysis, with

congruence with the other four. Therefore, institutions provide standards for the

organisation to reduce uncertainty and to operate in complex situations. Accounting is

an institutional mechanism to reduce transaction costs, information asymmetry, lower

coordination costs, improve enforcement of property rights and facilitate complex

transaction in an economy (North 1990; Watts & Zimmerman 1978; Wysocki 2011).

The use of accounting and auditing in collecting debt and in contract enforcement help

to facilitate economic development (North 1990; Watts & Zimmerman 1978). The next

section will define new institutional theory from a sociological view of institutions.

1 Institutions norms, rules, conventions, habits and values

2 Institutional

arrangements

markets, state, corporate hierarchies, networks,

associations, communities

3 Institutional sectors financial system, system of education, business system,

system of research, social system of production

4 Organisations

5 Output

and performance

statutes, administrative decisions, the nature, quantity

and quality of industrial products, sectoral and societal

performance

Source: Hollingsworth (2003, p.133)

7Table 5.1: Components of institutional analysis

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5.4.2 New institutionalism - new institutional theory

‘New institutionalism’ developed in the mid-1980s and revived the concept of

institutions with proliferation of interest in economics, sociology, international relations

and political science (Scott 2008). Powell and DiMaggio (1991) mentioned old and new

institutionalism approaches in identifying different sources of constraint for

organisational rationality, shown in Table 5.2.

Old institutionalism New institutionalism

Conflicts of interest Central Peripheral

Sources of inertia Vested interests Legitimacy imperative

Structural emphasis Informal structure Symbolic role of formal

structure

Organisation embedded in Local community Field, sector, or society

Nature of embeddedness Co-operation Constitutive

Locus of institutionalisation Organisation Field or society

Organisational dynamics Change Persistence

Basis of critique of

utilitarianism

Theory of interest

aggregation

Theory of action

Evidence for critique of

utilitarianism Unanticipated consequences

Unreflective activity

Key forms of cognition Values, norms, attitudes Classifications, routines,

scripts, schema

Social psychology Socialisation theory Attribution theory

Cognitive basis of order Commitment Habit, practical action

Goals Displaced Ambiguous

Agenda Policy relevance Disciplinary

Source: Powell and DiMaggio (1991, p.13).

8Table 5.2: The new and old institutionalism

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5.4.3 Significance of institutional isomorphism

Bischof, Brüggemann and Daske (2010, p.509) define isomorphism as the ‘adaption of

institutional practices by an organisation’. Hawley (1968) defined isomorphism as ‘a

constraining process that forces one unit in a population to resemble other units that

face the same set of environmental conditions’ (DiMaggio & Powell 1983, p.151). The

diversity of organisational forms in a population is isomorphic to environmental

diversity (DiMaggio & Powell 1983). Hannan and Freeman (1977) argued that

isomorphism could result as organisational decision-makers learn and respond

appropriately to adjust their behaviour. Institutional isomorphism is a relevant notion

for understanding the politics and factors that influence the modern organisation

(DiMaggio & Powell 1983).

Institutional isomorphism is concerned with legitimacies and strategies that are

acceptable and appropriate to society and creates organisations with similar conditions

(Laux & Leuz 2009). According to DiMaggio and Powell (1983, p.148), ‘once disparate

organisations in the same line of business are structured into an actual field……..

powerful forces emerge that lead them to become more similar to one another’.

Organisations within an industry tend to resemble each other structurally or become

‘isomorphic’ as a result of exposure to similar societal pressures being exerted by the

powerful stakeholder groups (DiMaggio & Powell 1983).

New institutionalism theorists (Meyer 1977, Fennell 1980, DiMaggio & Powell 1983)

discuss two forms of isomorphism: competitive and institutional. Competitive

isomorphism implements a system rationality that emphasises market competition,

change of function, measures the fitness of the organisation and exists in a free

competitive environment (DiMaggio & Powell 1983). In contrast, institutional

isomorphism influences organisations when they operate in a political power and

institutional legitimacy environment (Hawley 1968, Hassan 2008, DiMaggio & Powell

1983).

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Bangladesh, among the developing countries, marked the beginning of an evolution

in its financial reporting through “ adopting” international standards after the GFC.

However, compliance remains effectively voluntary with little consequence for non-

compliance. The implementation of international standards is motivated largely

according to countries’ institutional settings, along with their economic, political and

social frameworks. Developing economies are often characterised by family dominance,

a high level of corruption and significant political interference and, therefore, are not

conducive to adoption of Western-styled governance models (Uddin & Choudhury

2008).

5.4.4 Isomorphism processes

DiMaggio and Powell (1983) identified three institutional isomorphic processes:

coercive, mimetic and normative. These three forms of institutional isomorphism are

powerful theoretical foundations within the accounting literature in investigating

organisational responses to changing institutional pressures and expectations (Lenckus

2001). For example, Carpenter and Feroz (2001) investigate the selection of government

accounting practices within the theoretical perspective of coercive isomorphism.

5.4.4.1 Coercive isomorphism

Coercive isomorphism is defined as ‘both formal and informal pressures exerted on

organisations by other organisations upon which they are dependent and by cultural

expectations in the society within which organisations function’ (DiMaggio & Powell

1983, p.150). In the accounting perspective, formal coercive isomorphism is exercised

through financial reporting and disclosure standards (Gordon, Loeb & Tseng 2009).

Institutional pressure creates formal coercive isomorphism through the ensuing rules,

regulations and legitimacy (Scott 2004). Such pressures derive from governmental

directives, existing laws, regulation and financial reporting requirements which have an

impact on organisational changes towards homogeneity within the given domain and

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ritual to wider institutions (DiMaggio & Powell 1983). However, informal coercive

isomorphism forms through persuasion or invitation to join in collusion (DiMaggio &

Powell 1983). For example, finance providers can influence more transparent reporting

(Hassan 2009). DiMaggio and Powell (1983) also argued that the extent of coercive

isomorphism is associated with the extent to which one is dependent on others in terms

of individual and organisational level.

Laux and Leuz (2009) argued that societal and cultural expectations coerce

organisations to ensure legitimacy as they create a ‘social contract’ between the social

context and organisation. They also drive organisations to adopt socially acceptable

practices (Laux & Leuz 2009).

According to Tuttle and Dillard (2007, p.393), coercive isomorphic ‘change is imposed

by an external source such as a powerful constituent (e.g., customer, supplier,

competitor), government regulation, certification body, politically powerful referent

groups, or a powerful stakeholder’. Therefore, powerful stakeholders in adopting

organisational practices coerce other organisations. Lenckus (2001) argued coercive

isomorphism stems from the ‘power’ of stakeholders to exert pressure on organisations.

For example, stakeholder groups such as investors can coerce organisations to report

risk as companies are dependent on their finance resource.

Previous studies suggest that bank creditors (i.e. depositors) mandate disclosure

transparency (Barth, Caprio Jr & Levine 2004). Therefore, companies disclose a greater

level of risk disclosure to explain the causes of high level risks to creditors (Linsley &

Shrives 2006). The more the bank depends on debt financing, the more likely the

creditors’ power is exercised in risk reporting (Barth & Landsman 2010; Barth &

McNichols 1994; Cormier, Gordon & Magnan 2004). In a highly leveraged company,

creditors may demand more disclosure of information to understand the risk profile of

the business (Ahn & Lee 2004).

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The theoretical perspective discussed within the coercive isomorphism concept

underlines that organisations are coerced by other more leading organisation as they are

dependent. This study hypothesises that depositors’ and investors’ coercive

isomorphism influences banks to provide more risk disclosure. Therefore, it is predicted

that more highly geared banks provide more risk disclosure than less geared banks.

H5: Coercive isomorphic pressures are positively associated with the extent of

risk disclosure.

5.4.4.2 Mimetic isomorphism

Industrial interdependencies can stem mimetic isomorphism (Powell & DiMaggio

1991). Organisations tend to model themselves on successful companies in the industry

to be perceived as more legitimate and successful (DiMaggio & Powell 1983). They

replicate as a mirror of other organisational practices those that are recognised ‘as

superior, as more successful’ (Gul & Leung 2004, p.45) and where ambiguity and

uncertainty arises, mimicking the organisational practices of a successful group is

recommended (Hassan 2009).

According to Tuttle and Dillard (2007, pp. 392-393), ‘change is voluntary and

associated with one entity copying the practices of another…….mimetic isomorphism

occurs when the processes motivated by these pressures become institutionalised so that

copying continues because of its institutional acceptance rather than its competitive

necessity’. That is, organisations imitate other organisations’ practices to improve

performance. Successful companies adopt disclosure practices to increase the

probability of survival. These adoption processes create social pressure to foster similar

organisational practices and policies among organisations, leading them to become

more isomorphic in order to comply with societal requirements (DiMaggio & Powell

1983; Scott 2008).

Gani and Jermias (2006, P.472) identified three distinctive modes of mimetic

isomorphism: ‘frequency imitation (copying very common practices), trait imitation

(copying practices of other organisations with certain features) and outcome imitation

(imitation based on a practice’s apparent impact on others)’. An organisation executes

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frequency imitation by following practices used previously by a large number of other

organisations. Therefore it is merely a modal decision (Holder-Webb & Cohen 2007).

With trait imitation, certain traits are mimicked, such as large size. Outcome based

imitation follows the past good outcomes of other organisations and avoids bad

outcomes (Gani & Jermias 2006).

DiMaggio and Powell (1983) argued that mimetic isomorphism derives from

organisational uncertainty when the organisational technologies are understood poorly

or goals are ambiguous. Uncertainty causes mimicking behaviour and imitation of

successful organisations. Mimetic isomorphism may take place and be diffused

unintentionally, diffused indirectly through employee transfer or turnover, or diffused

explicitly through industry trade organisations (DiMaggio & Powell 1983). Thus, the

coercive isomorphism concept underlines the notion that organisations may model

themselves on others by adopting disclosure practices and in turn influence others in the

industry.

Previous studies have applied the theoretical concept of mimetic isomorphism in

examining, for instance, how corporate social responsibility is influenced by disclosure

practices adopted by other organisations (Bushman et al. 2004). Moreover, existing

studies have found that large rather than small banks characterise themselves by

disclosing more risk information which results in reduced monitoring costs and reduced

information asymmetry (Abraham & Cox 2007; Aebi, Sabato & Schmid 2012; Oliveira,

Rodrigues & Craig 2011). In addition, a higher extent of disclosure assists superior

companies to be more evident to relevant shareholders (Mashayekhi & Bazaz 2008).

Larger banks compared to smaller banks consider a higher level of risk disclosure to

imply closer scrutiny from stakeholders and thus enhancing of corporate reputation

(Amran, Bin & Mohd 2008; Oliveira, Rodrigues & Craig 2011). The discussion leads to

the hypothesis that mimetic isomorphism of larger banks has an influence on the degree

of risk reporting by smaller banks. However, as the influence of larger banks on smaller

banks is not testable empirically in a robust way, qualitative data is analysed to provide

evidence in support or refutation.

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H6: Mimetic isomorphism of larger banks influences smaller banks to provide

more risk disclosure.

5.4.4.3 Normative isomorphism

DiMaggio and Powell (1983, p.152) defined normative isomorphism as ‘a third source

of isomorphic change …and stems primarily from professionalisation, which is defined

as the collective struggle of members of an occupation to define the condition and

methods of their work’. Experienced managers execute their specialised knowledge,

education and practical professional networks in the organisation.

Normative pressure is exerted through professionalisation by abiding common

standards, common educational background and professional socialisation. Normative

isomorphism forces professional influences on firm performance, resulting from

professional training and education. These employ social practices, such as financial

reporting disclosure among organisations in the industry (Hassan 2009).

DiMaggio and Powell (1983, p.152) identified two aspects of professionalisation as a

source of isomorphism, ‘One is the resting of formal education and of legitimation in a

cognitive base produced by university specialists; the second is the growth and

elaboration of professional networks that span organizations and across which new

models diffuse rapidly’. University education and professional training organisations

develop norms among professional managers. They create norms and values in the

organisation that cannot be viewed objectively but are assumed to be true by

stakeholders (Farooque et al. 2007). For example, professional education and training

programmes influence the level of education of the members who eventually are

employed in the organisation.

Professional and trade associations are another means of diffusion of normative rules

about professional behaviour and override variation in tradition and control that in turn

outline organisational behavioural change (Bank 2012b). These mechanisms ‘create a

pool of almost interchangeable individuals who occupy similar positions across a range

of organisations’ (DiMaggio & Powell 1983, p.152). Therefore, organisations might

108

change to follow professional norms and organisational practices in relation to

disclosure practices.

Applying normative isomorphism, Cerbioni and Parbonetti (2007) found that chief

executive officers who attended elite business schools were likely to adopt an approach

to organising a business known as the multi-dimensional form of institution. In the

context of the theoretical aspects of normative isomorphism, the present study

hypothesises that if a bank has a dedicated Risk Management Unit, normative

isomorphic power is expected to be exercised. That is, stronger risk communication is

expected in annual reports of these banks compared to banks that do not have a Risk

Management Unit. The Risk Management Unit is charged uniquely with risk

management and monitoring processes and practices that inform risk information

provided to the banks’ section responsible for compiling the disclousre in the annual

report. The Hypothesis is:

H7: Normative isomorphism is positively associated with the extent of risk

disclosure.

5.5 The relation between risk disclosure and bank performance

As discussed in Chapter 1, the third Phase of this study investigates whether risk

disclosure has an association with bank performance. Effective governance mechanisms

are an attempt to facilitate stakeholders and managers, which reduce agency costs and in

turn improve organisations’ performance. As ‘conflict of interest’ is inherent in

shareholder-manager relationships, disclosure of information can help shareholder-

manager interests and therefore, improve firm performance (Bhagat & Bolton 2008;

Jensen & Meckling 1976; Weir, Laing & McKnight 2002). Healy and Palepu (2001)

argue that disclosure communicates firms’ governance and performance to users of

financial reports. Correspondingly, voluntary disclosure of risk governance practices

makes users of financial statements aware of banking stability and risk resilience by

allowing assessment of the bank’s risk profile. Beverly (2007) argues that greater

disclosure is associated with lower risk, and in turn improves the risk-return trade-off.

109

Previous studies argue and find evidence that voluntary disclosure is an essential

mechanism that enhances the organisation’s performance (Healy & Palepu 2001; Miller

& Noulas 1996). Several cross-country studies suggest that voluntary disclosure

increases bank monitoring that reduces sovereign risk (Bertus, John & Yost 2007;

Demirgüç-Kunt, Detragiache & Tressel 2008), assists greater banking development,

lower interest rate and smaller non-performing loans (Barth, Caprio & Levine 2004).

Fernández and González (2005) provide further evidence indicating that the efficiency

of accounting and auditing devices balances the capital requirements and additional

monitoring on banking undertakings.

In this study, bank performance is measured using two broad aspects; bank operating

performance and bank valuation. Bank operating performance is measured as employee

efficiency, solvency efficiency, deposit concentration, financial performance, and bank

valuation is measured using Tobin’s q and the book to market ratio.

5.5.1 Employee efficiency

Extant studies (Katz 1998; McElroy 2001) argued that organisational information has a

consistent positive impact on organisational performance. Organisational information

connects employees, aligns their goals with those of the organisation and thus creates

integration in the work place (McElroy 2001). Additionally, it increases employee

identification, commitment to work and creates long-term organisational success (Katz

1998). Risk disclosure of information by banks is particularly important as employees

become aware of banks’ risk exposure, and hence better able to assess banks’ risk-

taking profile. The Hypothesis in this study is:

H8: Employee efficiency is positively associated with the extent of risk

disclosure.

5.5.2 Solvency efficiency

Disclosure of risk information is expected to result in higher solvency efficiency as it

allows stakeholders to assess risk and favourable managerial actions. Extant studies

110

argue that financial disclosure is a primary tool for market discipline and market

discipline has a positive association with bank solvency efficiency (Botosan 2004;

Verrecchia 2001). Richardson and Welker (2001) argue that market efficiency depends

on comprehensive and value-relevant, transparent disclosure. They argue that disclosure

benefits firms through lower cost of capital because of two aspects; first, disclosure

reduces transaction costs. Greater disclosure assists potential investors to overcome

hostile choice of bid-ask spread33

and reduces the cost of capital (Botosan 1997). More

disclosure reduces adverse price impacts associated with large trades and reduces

information asymmetry to investors, which leads to higher demand for securities in the

market, reduces transaction costs and improves solvency, in turn reducing the cost of

equity capital (Amihud 1986; Botosan 1997; Verrecchia 2001). Second, increased

disclosure reduces uncertainty or estimation risks (Clarkson, Guedes & Thompson

1996). Botosan (1997) argued that extant research suggests that greater disclosure

decrease the cost of equity capital. Extant studies (Demirgüç-Kunt, Detragiache &

Tressel 2008; Goddard, Molyneux & Wilson 2009) argue that well funded banks face

inferior insolvency costs and therefore lower subsidy costs. The next Hypothesis is:

H9: Solvency efficiency is positively associated with the extent of risk disclosure.

33

Bid-ask spread is the amount by which the ask price exceeds the bid. This is essentially the difference

in price between the highest price that a buyer is willing to pay for an asset and the lowest price for which

a seller is willing to sell it (see online at http://www.investopedia.com/terms/b/bid-askspread.asp)

http://www.investopedia.com/terms/b/bid-askspread.asp

111

5.5.3 Deposit concentration

Stakeholders are concerned with bank strategies and respond accordingly to risk

exposure (Nier & Baumann 2006). The banking industry is characterised by high asset

investments. Frolov (2004) argued that;

….asset opacity is in the nature of the banking business, and it amplifies the banks’

incentive to moral hazard and creates conditions for their profiting at the expense of

uninformed creditors. But better bank disclosure can curtail the moral hazard both ex

ante and ex post. With the ex-ante effect, the funding cost of risky institutions gets

higher as potential depositors and other creditors appreciate the banks’ (disclosed)

financial condition. When ex post, the banks’ risk-taking is disciplined by costs inflicted

by en mass withdrawals of deposits from the risky institutions or just a threat of a run on

them (p.9).

The above argument is supported by Beverly (2007). He explained the ex-ante effect of

risk disclosure is such that the cost of capital for risky institutions becomes higher than

for less risky institutions. However, banks are inherently risky ventures and less risk

disclosure may generate ambiguity for potential stakeholders. Deposit concentration

should therefore be higher with banks that provide high levels of risk disclosure since

disclosure reduces uncertainty for depositors. Therefore, the next Hypothesis is;

H10: Deposit concentration is positively associated with the extent of risk

disclosure.

5.5.4 Financial performance

Extant studies have found that financial disclosure has a positive impact on bank

performance. For example, Verrecchia (2001) examined extant literature on disclosure

and found greater disclosure practices benefit the firm by high market liquidity.

Botosan (1997) argued increased financial disclosure benefits manufacturing firms

(industrial and commercial machinery) by decreasing the cost of capital. Callahan and

Smith (2004) found that financial disclosure is positively associated with current and

future performance in the banking industry. While these studies do not focus on risk

disclosure, especially not on risk disclosure in a banking institution setting, this study

112

expects to find an association between the extent of risk disclosure and financial

performance. Therefore, the next Hypothesis is;

H11: Financial performance is positively associated with the extent of risk

disclosure.

5.5.5 Risk disclosure and bank valuation

As discussed in the previous section, extant research has found a positive association

between financial disclosure and operating performance. Botosan (1997) suggests that

financial disclosure has the potential to change bank valuations by reducing the cost of

capital. Nier and Baumann (2006) examined banks from 32 countries (729 individual

banks) around the world and found higher disclosure results in lower bank stock price

volatility. Foerster, Sapp and Shi (2013) found that disclosure of earnings by

management by Canadian firms is positively associated with firm value in two aspects;

reduced firm risk and change in investors’ perceptions about future cash flows. Healy

and Palepu (2001) argued financial disclosure increases bank transparency, reduces

uncertainty and help investors’ correct firm valuations. The logical extension to these

arguments is that rational market participants would appreciate greater disclosure.

Therefore, the next hypothesis is;

H12: Bank value is positively associated with the extent of risk disclosure.

5.6 Conceptual framework

The underpinning theories discussed in this Chapter (sections 5.3 and 5.4) depict the

conceptual framework for this study as shown in Figure 5.3. The Figure depicts that

agency theory and institutional isomorphism assist in explaining the motivation of

managers to provide corporate risk disclosure.

113

A larger proportion of independent directors on the board is positively associated with a

higher level of disclosure and therefore, is effective as a monitoring process (Beretta &

Bozzolan 2004; Cheng & Courtenay 2006; Lajili 2009; Lopes & Rodrigues 2007).

These directors have incentives to demand greater risk disclosure to balance the level of

risk in the business and thereby attain or retain their personal reputation (Amran, Bin &

Mohd 2008; Beasley, Clune & Hermanson 2005; Oliveira, Rodrigues & Craig 2011). In

addition, audit committees review the risk management, internal control and compliance

processes of business. Independent directors on the audit committee increase the

effectiveness and reliability of the audit committee (Turley & Zaman 2004). Therefore,

banks with a higher ratio of independent directors on the audit committee can be

17 Figure 5.3: Conceptual framework for this study

Coercive

isomorphism

Normative

isomorphism

Mimetic

isomorphism

Bank value

Extent of

risk

disclosure

Agency

Theory

Institutional

Isomorphism

Board

Independence

Audit Committee

Independence

Risk Committees

H2

H3

H4

H5

H6

H7

H12

H1

Employee

efficiency

Solvency

efficiency

Financial

Performance

Deposit

concentration

H9

H8

H10

H11

Bank

Performance

114

expected to place greater attention on reporting risk disclosure than those with a lower

proportion (Oliveira, Rodrigues & Craig 2011).

Figure 5.3 also infers that risk committees assist by measuring, monitoring and

maintaining an acceptable level of risk. Dedicated risk committees monitor risk

exposure, policies and procedures affecting loans, non-performing loans, market, and

operational areas efficiently within risk strategy and risk appetite established by the

board of directors. Under the institutional isomorphism concept, this study hypotheses

that coercive and institutional isomorphism processes influence bank’s risk reporting.

This research will further examine the association of risk disclosure with bank

performance (financial performance, employee productivity, solvency efficiency, and

depositors’ concentration and bank valuation).


This Chapter discusses the underpinning theories for this study in relation to achieving

its objectives. The discussion of agency theory and institutional isomorphism suggests

risk disclosure motivations. The underlying theoretical foundation within this Chapter

suggests that banks can be seen to provide corporate risk disclosure for accountability to

wider stakeholder groups. Having discussed the relevant theoretical perspectives, a

conceptual framework is developed. The specific application of these theories is

investigated in Part Four (Analysis) of this thesis. Prior to that, the next Chapter

describes the research method employed to conduct the three Phases of this study.

116

PART THREE

METHODOLOGY

Chapter 6: Research Methodology

117

Part Three of this thesis illustrates the methods and methodology used in this research.

Chapter 6 presents a detailed discussion of the methodological approach adopted in this

research. This study is designed using a mixed method approach, employing both

qualitative and quantitative data collection and analysis. Secondary data is used for the

quantitative analysis while interviews are conducted using a semi-structured protocol

for the qualitative analysis. It is argued in this thesis that detailed investigation using

both the qualitative and quantitative methods applied enhances understanding of the

research problem surrounding risk reporting behaviour in the banking industry and

results of testing in a way superior to either approach alone.

118

CHAPTER 6: Research Methodology

6.1 Introduction

The previous Chapters discussed the literature, research questions, the theoretical

framework and the Hypotheses for this study. Research design is a significant part of

any research project as the quality of the research depends on the adoption of

appropriate methodologies, collection of data with integrity and the research paradigm.

The purpose of this Chapter is to describe the research design and methodological

assumptions adopted in this study.

This Chapter provides a detailed discussion of the quantitative and qualitative methods

adopted, including of the research instrument, sampling design, data collection and

analysis process procedures. The ethical issues surrounding confidentiality of

qualitative interview data considerations is discussed at the end of this Chapter. Figure

6.1 provides an overview of this Chapter.

The remainder of this Chapter proceeds as follows. The ontological and

epistemological assumptions are discussed in section 6.2. Following this discussion of

the philosophical assumptions, a discussion of descriptive, exploratory and explanatory

types of research appears in section 6.3. A rationale for the theoretical perspective

18 Figure 6.1 Roadmap of Chapter

Introduction (6.1) Philosophical

assumptions (6.2)

Research type

(6.3)

Theoretical

perspective (6.4)

Methodology (6.5)

Chapter conclusion

(6.9) Ethical clearance

(6.8)

The qualitative

method (6.7)

The quantitative

method (6.6)

119

adopted is discussed in section 6.4. Followed by research methodology, the

triangulation process and research paradigm in sections 6.5, 6.6 and 6.7 establish the

quantitative and qualitative methods adopted, including justification for the population

identification, the sampling approach, the research instrument, and the analysis

framework employed. Ethical issues of confidentiality surrounding the interview data

are discussed in section 6.8 and the Chapter concludes in section 6.9.

6.2 Philosophical assumption

A philosophical assumption is associated with every research approach. The research

paradigm provides the foundation of the research methodology and methods used in the

study. Veal (2005) argued a research paradigm as a shared framework of assumptions

that reflect a basic set of philosophical beliefs about the nature of the world and

provides guidelines and principles concerning the way of research. Different research

paradigms are used in the literature. The most commonly used research paradigmatic

dichotomies are described in Appendix 6.1. The selection of the research paradigm

depends on ontological assumptions (the basic belief) and epistemological assumptions

(valid knowledge).

A research paradigm is a linking of ‘ontology’, ‘epistemology’ and ‘methodology’.

(Tashakkori & Teddlie 2010). The research strategy is guided by understanding and the

nature of reality (ontology) and the knowledge achieved within the paradigm

(epistemology) (Newholm & Shaw 2007). Ryan, Scapens and Theobald (2002)

explained;

…the assumptions that the researcher holds regarding the nature of the phenomenon’s

reality (ontology), will affect the way in which knowledge can be gained about the

phenomenon (epistemology), and this in turn affects the process through which research

can be conducted (methodology). Consequently, the selection of an appropriate research

methodology cannot be done in isolation of a consideration of the ontological and

epistemological assumptions, which underpin the research in question (p.35).

120

The following sections discuss ontological, epistemological and methodological

assumptions and the relevance of these to this study.

6.2.1 Ontological assumption

An ontological assumption is the belief about the way ‘reality’ is perceived. Morgan

and Smircich (1980) provided a continuum of basic ontological assumptions. Figure 6.2

shows the scale;

Source: Adapted from Morgan and Smircich (1980), p. 492.

The ‘Continuum of Ontological Assumptions’ is explained by Ryan, Scapens and

Theobald (2002). They illustrate ‘reality’ as characterised by external objective ‘facts’

about the world defining a set of variables and laws. In addition, evaluation and human

beings’ activities (e.g. continuous process, learning and adoption of new environments)

increase social interaction, norms and behaviour. The role of accounting also provides

norms and structure for day-to-day behaviour and practices within organisations and

society. As a result, concrete reality moves to an open system for individuals and

society. Individuals and society make sense of accounting information and explore the

depth of information. Thus, the social world is recreated and confronted with the

complexity of societal reaction to information.

The ontological assumptions in this research are between the two extremes of this

continuum. Consistent with the aim of this research, this study analyses ‘objectively’

the annual reports of banking institutions in Bangladesh. Additionally, using in-depth

interviews, this study analyses the perceptions of managers and regulators within the

banking industry ‘subjectively’ to better understand the issues associated with risk

19 Figure 6.2: Continuum of ontological assumptions

Objectivist Subjectivist

Reality as a

concrete

structure

Reality as a

concrete

process

Reality is a

contextual

field of

information

Reality as a

realism of

symbolic

disclosure

Reality as a

social

construction

Reality as a

projection of

human

imagination

121

reporting and provide evidence-based solutions. Therefore pragmatic post-constructivist

ontology is used to understand the real practices of risk reporting, the underlying factors

of risk reporting and the effect of risk reporting on bank performance.

6.2.2 Epistemological assumption

‘Epistemology’ is the way knowledge is to be acquired in connection with truth, belief

and justification. Ryan, Scapens and Theobald (2002, p.11) explain that ‘knowledge

creates three substantive issues: the nature of belief, the basis of truth and the problem

of justification’. This section discusses epistemological perspectives including

‘constructivism’ and ‘objectivism’ in the context of this research. Crotty (1998)

explained a constructivism epistemological position as:

...all knowledge, and therefore all meaningful reality as such, is contingent upon human

practices, being constructed in and out of interaction between human beings and their

world, and developed and transmitted within an essentially social context (p.42).

Therefore, human attitudes, beliefs and values construct perceptions of the event

(Tashakkori & Teddlie 2010). Constructivism is relevant in this research as the ‘Risk

Disclosure Index’ (RDI) developed in this research can change according to the

attitudes and behaviour of key stakeholders. As a result, constructivism proves to be a

valuable research framework for this study.

Objectivism epistemology deals with ‘things exist as meaningful entities independently

of conciseness and experience that have truth and meaning residing in them as objects

and that careful research can attain that objective truth and meaning’ (Crotty 1998, pp.5-

6). As mentioned earlier, the Risk Disclosure Index developed in this research is based

on international standards (IFRS 7 Financial Instruments: Disclosures and BASEL II:

Market Discipline) and is used to examine the risk reporting practices of banking

institutions. Additionally, the theoretical framework adopted and the Hypotheses

developed in this study aim to achieve the research objectives. Therefore, both

constructivism and objectivism constitute the epistemological perspectives of this study.

122

6.3 Research type

The philosophical assumption adopted for research directs choosing appropriate

methods for its conduct. The philosophical stance establishes the ontological and

epistemological assumptions for this study. According to Collis and Hussey (2003) the

choice of research paradigm has implications for selecting the research methodology

(research approaches) and methods (e.g. data collection technique). Research can be

seen from three different perspectives, being application, objective and mode of inquiry

(Kumar 2011). The research types are discussed as ‘Exploratory’, ‘Descriptive’,

‘Analytical’ or ‘Explanatory’ and ‘Predictive’ (Collis & Hussey 2003); ‘Exploratory’

and ‘Evaluative’ (Veal 2005). The definitions for these different research types can be

found in Appendix 6.2. The rationale for selecting the research type is based on the

research aim(s) and purpose (Veal 2005).

To attain the research objectives, this study is in part descriptive, observing and

informing the reader of the level of risk reporting practices in annual reports issued by

banks. Additionally, to seek further explanation and exploration of antecedent factors of

risk reporting, this study includes interviews with managers and regulators within the

banking industry and analysis of the determinants of risk reporting and. That is, this

study employs a mix of descriptive, analytical/explanatory and exploratory types of

applied research, using both qualitative and quantitative data.

6.4 Theoretical perspective

The theoretical perspective relates to the underlying philosophical assumptions behind

the researcher’s view of the human world and the social life within that world (Crotty

1998). The two broad theoretical perspectives of research are positivism and

interpretivism. Reflecting objectivism epistemology, positivism discovers scientific

laws to explain causes and consequences of the phenomena being investigated.

However, based on constructivism epistemology, interpretivism suggests understanding

inherent differences as people interpret the social world in various ways (Marsh et al.

2009).

123

The philosophical assumption adopted by this researcher has served to encourage

employing a mixed method of research. The theoretical perspectives adopted in this

study require objectively viewing the positivism paradigm using a quantitative approach

and assessing subjectively the interpretivism paradigm using a qualitative approach.

Mixed method research works with both narrative and numeric data for their analysis

and when data are of mixed natures, a more accurate picture emerges (Teddlie &

Tashakkori 2009). However, mixed method research is less well known than

quantitative or qualitative research (Creswell 2003; Teddlie & Tashakkori 2009).

6.5 Methodology

This section presents the overall approaches used in this research. As mentioned above

this study employs a mixed method strategy to validate the research objectives (Crotty

1998). According to Bryman and Bell (2007), the quantitative and qualitative

approaches comprising the mixed method should be explained separately.

6.5.1 Quantitative research approach

Quantitative research is dominant in social, psychological, behavioural sciences and

business (Veal 2005). Quantitative research involves collection of numerical data and

exhibits the relationship between theory and research in a deductive and positivist

approach (Bryman 2012; Collis & Hussey 2003; Veal 2005). The advantage of

quantitative research is that findings can be generalised beyond the confines of a

particular context in which the research was conducted. However, quantitative research

is criticised as the approach fails to understand people and social institutions from ‘the

world of nature’ (Bryman 2012, p.178). Common methods applied to collect

quantitative data are surveys, observations, experimental studies, and secondary data

(Veal 2005).

124

6.5.2 Qualitative research approach

Qualitative research is defined as naturalistic, ethnographic, anthropological and social

observer, emphasising the natural settings of variables using interpretivist and

constructivist paradigms. Bryman (2012) explains qualitative research as an inductive

approach with a ‘view of the relationship between theory and research’ using

‘interpretivist’ (epistemological) and ‘constructionist’ (ontological) stances. Qualitative

research enables researchers to reach an in-depth understanding of the phenomena.

However, the criticism of this type of research is that it is ‘too impressionistic and

subjective’ (Bryman 2012, p.405). Qualitative data can be obtained from interviews,

case studies, narrative inquiry or participant observation (Patton 2002; Veal 2005).

6.5.3 Mixed method approach

A mixed method research combines quantitative and qualitative research within a single

project (Bryman 2012; Tashakkori & Creswell 2007; Veal 2005). More specifically,

mixed method has been defined by Tashakkori and Creswell (2007) as;

..research in which the investigator collects and analyses data, integrates the findings,

and draws inferences both qualitative and quantitative approaches in a single study or

program of inquiry (p.4).

This approach is relatively new and has been used increasingly in social research since

the early 1980s. Mixed method research involves collecting both quantitative and

qualitative data either simultaneously or sequentially to best understand the research

problems (Creswell & Clarke 2011; Tashakkori & Creswell 2007). A mixed method

approach enhances understanding of the research problem in-depth and confirms the

findings from different sources of data (Creswell & Clarke 2011). Hence, a mixed

method approach provides a detailed view of individual phenomena; the researcher can

capture an in-depth picture of the context using secondary quantitative data and follow

up the meaning of insights to the phenomena using semi-structured interviews

(qualitative data).

125

6.5.4 Paradigm adopted in this study

The choice of research methodology depends on the purpose of a particular type of

research (Veal 2005). Recognising the limitations of both qualitative and quantitative

methods, researchers felt that the inherent bias of any single method could neutralise or

cancel the bias of other methods (Creswell & Clarke 2011). Additionally, the findings

using multiple research methods provide broader insights into the research problem

(Veal 2005). The qualitative and quantitative approaches address a range of

confirmatory and exploratory questions using better inferences and greater assortment

of divergent views (Tashakkori & Teddlie 2010; Teddlie & Tashakkori 2009). Hence,

the researcher prefers choosing suitable tools for data collection and analysis involving

both qualitative and quantitative methodologies rather than restricting to one

methodology. Therefore, this study employs mixed method strategies to achieve the

research objectives. The paradigmatic concerns and the research approaches are

summarised in Table 6.1.

As this research investigates the current level of risk disclosure practices in Bangladesh,

this study employs secondary data for its quantitative approach. Secondary data for this

research is easily accessible and uniformity of data can be achieved. Additionally, the

qualitative approach in this research is conducted using semi-structured interviews to

gain insights to factors underlying risk disclosure. Thus, interviews conducted with the

banking regulatory experts and senior managers in the risk reporting sections of banks

9 Table 6.1 Paradigmatic concerns and research approaches

Paradigmatic concerns Approach adopted

Ontological Perspective Post-constructivist

Epistemology Both constructivism and objectivism

Theoretical Perspective Positivism and interpretivism

Methodology Quantitative and qualitative

Method Content analysis and in-depth interviews

126

potentially provide a deep understanding of risk disclosure practices in the banking

sector in Bangladesh. Therefore, a mixed method method is appropriate to answer the

research questions and it is suitable for investigating risk disclosure antecedents and

their effects.

6.5.5 Designing triangulation in mixed method research

The best-known and commonly used approach in mixed method research is

triangulation (Creswell & Clarke 2011). It has been said that: ‘triangulation is worthy in

mixed method as congruent results from more than one method afford greater

confidence in the inferences to be made’ (Tashakkori & Teddlie 2010, p.125). Thus

triangulation involves more than one research approach in a single study to reach a

complete understanding of the research problem and enhance confidence in the ensuing

findings (Bryman 2012; Veal 2005). Hence, the associated limitations of one method

can be complemented by the prospects of another method.

Designing research for a mixed method approach triangulation is a challenging process

in identifying approaches to use in determining objectives of the study and in finding

the proper reasoning for the mixed method study. Creswell and Clarke (2011) defined

six types of design in the mixed method approach. Appendix 6.3 summarises the

prototypical characteristics of mixed method designs including convergent, explanatory,

exploratory, embedded, transformative, multiphase, concurrent, sequential and

transformative designs.

To achieve the research objectives of this study the qualitative and quantitative data

were collected concurrently and the results are converged by comparing and validating,

confirming or corroborating quantitative with qualitative findings (Bryman 2012;

Creswell & Clarke 2011; Tashakkori & Teddlie 2010). Therefore, the convergence

model of triangulation was used to collect and analyse quantitative and qualitative data

in this research. The next section presents the convergence model developed for this

study.

127

6.5.6 The convergence model of triangulation

The convergence model is most common, well validated and provides substantiated

findings in mixed method approaches (Creswell & Clarke 2011). Additionally, Creswell

& Clarke (2011) mentioned that the advantage of using a convergence model is that

separating quantitative and qualitative data concurrently offsets the inherent weakness

in one method with the strength of the other method. Thus, the weakness in generalising

from the qualitative interviews is complemented by the strength of accessible, accurate

quantitative data (secondary data). Further, it is important to note that a rich and

dynamic understanding of the insights are gained from additional findings from

interviews, which offset the weaknesses of analysing quantitative data. Figure 6.3

presents the convergence triangulation design used in this study

Source: Creswell and Clarke (2011).

Figure 6.3 shows how both the qualitative and quantitative data were collected

concurrently and then compared and contrasted to determine the convergence,

difference or combination (Creswell & Clarke 2011). As mentioned earlier, quantitative

data were collected from published annual reports of banks (secondary sources); and

interviews were conducted with senior managers (from banks’ Risk Reporting Units)

from listed banks and regulatory experts from the Central Bank and Bangladesh

Securities and Exchange Commission. The data from these two approaches were

collected concurrently and the results are compared, contrasted or combined to explore

the research questions in more detail.

20 Figure 6.3: The convergence model used in this study

Qualitative

data Analysis

Quantitative

data

collection

Quantitative

data Analysis

Qualitative

data

collection

Results

compared

and

contrasted

Interpretation

Quantitative +

Qualitative

128

The convergence model is appropriate in this study as secondary data were collected

and interviews were conducted in parallel to understand the extent of risk disclosure

practices, the factors underlying risk reporting and the association of risk reporting with

bank performance. The insights arising from the combination of methods are usually

found in an interpretation or discussion section (Creswell & Clarke 2011).

A summary of the research methodology design, data collection and analysis

procedures using the convergence model are presented in Figure 6.4.

21 Figure 6.4: Summary of the research design

Research Problem (ONTOLOGY)

Research

Objectives

Research Question

Theory

Research Approach

Q

ua

lit

ati

ve

Q

ua

nt

ita

tiv

e

Content Analysis

using secondary

data

Quantitative

Positivism

Narrative

Analysis using in

depth interviews

Qualitative

Interpretivism

Constructivism Objectivism

Literature

Review

Epistemology

Theoretical

Perspective Methodology

Method/Research

technique

Analytic Method

Results

Inductive

approach using

thematic analysis

Deductive

approach using

statistical

analysis

Both qualitative and quantitative data integration, analysis and discussion of the overall Results

Research

hypothesis

129

6.6 The quantitative method

As mentioned earlier, this study involves use of a mixed methods research design. This

section describes the quantitative techniques and procedures used to collect data and test

the Hypotheses in detail.

The unit of analysis involved in the quantitative method in this study is individual listed

banks in Bangladesh. The annual reports of these banks were sought, collected and

analysed to measure their risk reporting practices. Annual reports are the most

appropriate communication source between stakeholders and companies (Abraham &

Cox 2007). In other words, the annual report makes publicly available risk information

about the company and ‘enables the reader to obtain a coherent risk picture without

difficulty’ (Linsley & Shrives 2005a, p.211). Therefore, this study investigates annual

reports as the best source of risk information. In order to capture this information

systematically a ‘Risk Disclosure Index’ (RDI) checklist is developed as one of the

major contributions of this study. This checklist includes qualitative and quantitative

information. This section outlines the sample selection, research instrument, and model

specification for analysis using multiple regression.

6.6.1 Research instrument

In determining the extent of risk disclosure in listed banks, this study uses a content

analysis approach; a technique used by observing and analysing documents; such as

annual reports. The content analysis approach was chosen as this study focuses on the

extent and nature of risk disclosure in banks’ annual reports. As explained, this

approach is conducted in this research by creating a Risk Disclosure Index checklist.

6.6.1.1 Content analysis approach

The narratives in annual reports are examined using ‘subjective’ and ‘semi-objective’

analysis; a subjective approach is based on perception of the users and the semi-

objective approach is used commonly in disclosure studies (Beattie, McInnes &

Fearnley 2004). The semi-objective approach is used through content analysis (e.g.

130

disclosure index studies) and textual analysis (e.g. thematic content analysis, readability

studies or linguistic analysis) (Linsley & Lawrence 2007; Linsley, Shrives & Crumpton

2006). Figure 6.5 shows the narratives in annual reports.

Source: Adapted from Beattie, McInnes and Fearnley (2004), p.32.

Figure 6.5 illustrates the types of disclosure index studies specifying the items with

code in binary, ordinal, weighted unweighted or nested / un-nested form. Thematic

content analysis focuses on the topic or the theme disclosed in annual reports.

Readability studies provides a discussion of cognitive understanging of text and

linguistic analysis is study of the words used in the text. This study implements a

content analysis approach using a disclosure index checklist to capture banks’ risk

management disclosure.

22 Figure 6.5: Narratives in annual reports

Narratives in annual reports

Subjective-

usually analysts’

ratings

Characteristics of indices

Linguistic

analysis

Thematic content

analysis- a holistic

form of content

analysis where the

whole text is

analysed

Disclosure Index studies- A

partial form of content

analysis where the items to be

studied are specified ex ante

Textual analyses

Binary/

Ordinal

measure-

ment of

item

Weighted/

unweighted

Index

Readability

studies

Semi-objective

Nested/un nested

items (i.e.

grouping of items

into hierarchical

categories

131

Content analysis is a commonly used method in most of the previous disclosure

literature (e.g. Abraham & Cox 2007; Amran, Bin & Mohd 2008; Kajuter & Winkler,

2003; Linsley & Shrives 2006). Veal (2005) states that,

Content analysis involves detailed analysis of the content of a certain body of literature,

or other documentary sources which are viewed as texts ….. (and) examples are

company reports, the speeches of CEO and policy statements (p.84).

The limitations of content analysis are twofold (Beattie, McInnes & Fearnley 2004).

First, content analysis studies can be one dimensional, classifying only the presence or

absence of a feature. Second, they tend to be partial as they do not analyse the entire

content of an annual report. Moreover, content analysis is subjective. To overcome the

limitations of content analysis, this study uses a Risk Disclosure Index to screen for the

presence of risk disclosure items. Additionally, the Risk Disclosure Index was

developed in this study using a systematic approach to minimise subjectivity in the

analysis of narratives about risk included in annual reports. This systematic risk

disclosure framework is developed based on international standards and previous

literature.

6.6.1.2 Risk Disclosure Index

The Risk Disclosure Index used in this research is constructed based on a thorough and

rigorous study of International Financial Reporting Standards (IFRS) including IFRS 7:

Financial Instruments: Disclosures, the Basel recommendation of Pillar 3 for Market

Discipline and the risk disclosure literature. This index was applied to annual reports of

the sample banking institutions published over a 7-year period from 2006-2012.

Previous studies (Abraham & Cox 2007; Hassan 2009; Hernandez-Madrigal, Blanco-

Dopico & Aibar-Guzman 2012; Lajili 2009; Lajili & Zéghal 2005; Linsley & Shrives

2006; Nier & Baumann 2006; Uddin & Hassan 2011) use a risk disclosure index for

their content analysis. All these previous studies used an index based on subjectively

assembling the data from sample companies’ disclosures rather than an independent

source.

132

The inclusive Risk Disclosure Index in this study is based on international standards

(IFRS 7: Financial Instruments: Disclosures and Basel II: Market Discipline) and is

developed following two Phases. In the first Phase, an extensive review of prior studies

(e.g. Abraham and Cox 2007; Beretta and Bozzolan 2004; Cabedo and Miguel Tirado

2004; Lajili and Zéghal 2005; Linsley and Shrives 2006; Uddin and Hassan 2011)

provided the common items across the studies and identified the items for an initial

benchmark Risk Disclosure Index (49 items). These items were then categorised under

regulatory requirements (IFRS 7, Basel II: Market discipline). In the second Phase,

items (140 items including 42 common items, which were previously identified in

literature) from the regulatory framework requirements were included within the

benchmark Risk Disclosure Index. Thus, 14734

items in total constituted the Risk

Disclosure Index for this thesis. The Risk Disclosure Index includes seven key

categories; namely i) Risk types (Market, Credit, Solvency, Operational, and Equities);

ii) Capital disclosure; iii) Internal corporate governance ; iv) Information and

communication risks; v) Strategic decision risks; vi) General risk information; and vii)

Government regulation.

The Risk Disclosure Index consists of both qualitative and quantitative information.

Equal scores are allocated for each item; with ‘1’ point being assigned for disclosure

and ‘0’ for non-disclosure. The points are added to get a absolute score for each year.

The maximum score can differ for each bank according to its disclosures in the annual

report. The formula is;

Risk Disclosure Index by = MAXby

1

n

i

SCORE1

iby

Where: Risk Disclosure Index by = the risk disclosure score for bank (b) in the

year (y)

MAXby = The maximum possible score

i = Each item in the risk disclosure index

SCORE iby = The score for item i, bank b in year y.

34

147 items are calculated as 98(140-42)+49

133

This formula calculates the disclosure score for risk information for each bank by

dividing the total scores of all items of bank b by the maximum score bank b could

score. The result will be a score between 0 and 1. The scores thus scaled in this formula

can be compared with scores for other sample banks. Table 6.2 presents the Risk

Disclosure Index.

134

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.

Previous literature Ref.

A. Risk Types

MARKET RISK (Qualitative disclosure)

1. Exposures to market risk (MR) and how they arise 7.33 a

2. Structure and risk management function(s) MR 7.IG 15 Para824

3. Scope and nature of the entity's risk reporting or measurement systems of MR 7.IG 15 Para824

4. MR policies for hedging and mitigating risk, including policies and procedures for

taking collateral

7.IG 15 Para824

5. MR processes for monitoring the continuing effectiveness of hedges and

mitigating devices

7.IG 15 Para824

6. Methods used to measure MR 7.B7 Para824

7. MR policies and processes for on-and off-balance sheet netting Para824

8. Interest income and expense for MR 7.IG34 Abraham and Cox (2007); Lajili and

Zéghal (2005); Linsley and Shrives

10Table 6.2: Risk Disclosure Index

135

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


(2006)

9. MR maturity analysis of loans (i.e., 3months(m), 3m-6m, 6m-1yr,1yr-5yr, more

than 5yr)

Para824 Lajili and Zéghal (2005); Nier and

Baumann (2006)

10. MR maturity analysis of deposits; demand, savings(i.e., 3m, 3m-6m, 6m-1yr,1yr-

5yr, more than 5yr)

Para824 Nier and Baumann (2006)

11. Sensitivity analysis for currency risk 7.40 Para824 Lajili and Zéghal (2005)

12. Sensitivity analysis for others’ price risk 7.40 Para824

13. Method and assumption used in sensitivity analysis 7.40 Para824

14. Explanation of method used in preparing sensitivity analysis 7.41

15. Main parameters and assumptions underlying the data provided 7.41

16. Explanation of the objective of the method and parameters used 7.41

17. Terms and conditions of financial instruments 7.IG38

18. The effect on profit or loss if the terms or conditions were met 7. IG38

136

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


19. A description of how the risk is hedged 7. IG38

20. Information about trading financial and non-trading financial instruments 7.B17 (2)

21. Economic environment (hyperinflation or low inflation) 7.B17

22. Foreign exchange rates 7.IG32

23. Prices of equity instruments 7.IG32

24. Market prices of commodities 7.IG32

25. Prevailing market interest rate 7.IG33

26. Currency rates and interest rates for foreign currency financial instruments such

as foreign currency bonds

7.IG33

27.A description of how management determines concentrations 7.B8

28. If concentrated in one or more Industry sector (such as retail or wholesale) IG18 Para 825

29. If an entity concentrated on one or more credit quality (such as secured and

unsecured loans) and (investment grade or speculative grade)

IG18

137

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


30. Geographical distribution (such as Asia or Europe) IG18

31. A limited number of counterparties or group of closely related counterparties IG18

32. Key assumptions regarding loan prepayments and behaviour of no maturity

deposits

Para 824

33. Long term funding; convertible bonds, mortgage bonds, other bonds,

subordinated debt, hybrid capital

Para 824

34. Total money market funding

Para 824

MARKET RISK (Quantitative disclosure)

35.Summary quantitative data about exposure to MR at the reporting date (gross

market risk exposure, average gross exposure and major types of market exposure)

7.34 Para 825

36.Sensitivity analysis for interest risk 7.40

37.Sensitivity analysis for currency risk 7.40

38. Sensitivity analysis for other price risk 7.40

138

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


39. Amount of concentration of MR with shared characteristics (i.e. geographical,

region or country)

7.34,7.B

8 , IG19

Para 825

CREDIT RISK (Qualitative disclosure) Para 825

40. Exposures to credit risk (CR) and how they arise 7.33 Para 825

41. Structure and risk management function(s) 7.IG 15 Para 825

42. CR scope and nature of the entity's risk reporting or measurement systems 7.IG 15 Para 825

43. CR policies for hedging and mitigating risk, including policies and procedures

for taking collateral

7.IG 15 Para 825 Uddin and Hassan (2011)

44. Processes for monitoring the continuing effectiveness of hedges and mitigating

devices for CR

7.IG 15 Para 825

45. Methods used to measure CR 34, 7.B7 Para 825

46. CR policies and processes for on-and off-balance sheet netting Para 825

47. Loans by type (government, mortgage, lease, and other loans Nier and Baumann (2006)

139

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


48. Policies and processes for valuing and managing collateral and other credit

enhancements obtained

7.IG22 Lajili and Zéghal (2005); Nier and

Baumann (2006)

49. Description of main types of collateral and other credit enhancements 7.IG22 Para 824

50. Main types of counterparties to collateral and other credit enhancements and their

creditworthiness

7.IG22 Uddin and Hassan (2011)

51. Information about CR concentrations within the collateral or other credit

enhancements

7.IG22 Para 824

52. Nature and carrying amount of assets obtained by taking possession of collateral

held as security or called on other credit enhancements

7.38

53. Definitions of past due and impaired 7.12 (1) Para 824 Lopes and Rodrigues (2007)

54. The nature of the counter party 7.IG23 Para 824

55. Any other information used to assess credit quality 7.IG23 Para 824

56. Rating agencies used for external ratings when managing or monitoring credit

quality

7.IG24 Para 824

140

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


57.A description of how management determines concentrations for CR 7.B8


59. If an entity concentrated on one or more credit quality (such as secured and


IG18

60. Geographical distribution of CR (Asia or Europe) IG18 Nier and Baumann (2006)

61. A limited number of counterparties or group of closely related counterparties of

CR

IG18

62. The bank’s objectives in relation to securitisation activity, including the extent to

which these activities transfer CR of the underlying securitised exposures away from

the bank to other entities

Para824

63. Summary of accounting policies for securitisation activities, including: whether

the transactions are treated as sales or financings; recognition of gain on sale key

assumptions for valuing retained interests, including any significant changes since

the last reporting period and the impact of such changes

Para824

141

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


CREDIT RISK (Quantitative disclosure)

64. Summary quantitative data about exposure to CR at reporting date (gross credit

risk exposure, average gross exposure and major types of credit exposure)

7.34 Para 825

65. Amount of maximum exposure to CR (before deducting value collateral) 7.36

66. Granting financial liabilities, grantees should be significantly greater than

liability

7.B9

67. For loan commitment (irrecoverable over the life of the facility or recoverable

only in response to a material adverse change) the maximum credit exposure is the

full amount of the commitment

7.B10

68. Amount of concentration of CR with shared characteristics (i.e. geographical,

region or country)

7.B10

69.By class of financial assets, an analysis of the age of financial assets that are past

due as at the reporting date but not impaired. For example, time brands may be not

more than 3m, 3m to 6m, 6m to 1yr; and more than 1yr.

7.B10,7.

12

(1)

Para 825 Lopes and Rodrigues (2007)

70. Amount of credit exposures for each external credit grade 7.34,7.B Para 825

142

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


8 , IG19

71. Amount of an entity's rated and unrated credit exposures 7.35,

IG20

72. The total outstanding exposures securitised by the bank and subject to the

securitisation framework (broken down into traditional/synthetic), by exposure type

7.12 (1) Para 824

73. Aggregate amount of securitisation exposures retained or purchased, broken

down by exposure type

7.12 (1) Para 824

74. Loan loss reserves Para 824 Uddin and Hassan (2011)

75. Contingent liability Para 824 Uddin and Hassan (2011)

76. Off-balance sheet item Para 824 Uddin and Hassan (2011)

77. Loan loss provision

Para 824 Uddin and Hassan (2011)

LIQUIDITY RISK (Qualitative disclosure)

78. Exposures to liquidity risk (LR) and how they arise 7.33

143

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


79. Structure and risk management function(s), including a discussion of

independence and accountability for LR

7.IG 15 Para824 Lajili and Zéghal (2005); Lopes and

Rodrigues (2007)

80. Scope and nature of the entity's LR reporting or measurement systems 7.IG 15 Para824

81. LR policies for hedging and mitigating risk, including policies and procedures

for taking collateral

7.IG 15 Para824

82. LR processes for monitoring the continuing effectiveness of hedges and

mitigating devices

7.IG 15 Para824

83. Methods used to measure LR 34, 7.B7 Para824

84. LR policies and processes for on-and off-balance sheet netting Para824

85. judgement to determine an appropriate number of time bands (i.e. 0-1m, 1-3m,

3m-1yr, 1yr-5yrs)

7.B11 Lopes and Rodrigues (2007);Uddin

and Hassan (2011)

86. A maturity analysis of the expected maturity dates of both financial liabilities and

financial assets

7.IG30

87. Undrawn loan commitments 7.IG31

144

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


88. Readily available financial assets in liquid market to meet liquidity needs 7.IG31

89. Committed borrowing facilities (e.g., commercial paper) or other line of credit

(stand-by credit facility)

7.IG31

90. Financial assets for which there is no liquid market, but which are expected to

generate cash flows (principal or interest)

7.IG31

91. Deposits at central banks to meet liquidity needs 7.IG31

92. Diverse funding sources 7.IG31

93. Significant concentrations of liquidity risk (assets or funding source) 7.IG31

94. A description of how management determines concentrations of LR 7.B8


96. If entity concentrated on one or more credit quality (such as secured and


IG18

97. Geographical distribution of LR (Asia or Europe) IG18 Cabedo and Miguel Tirado (2004);

Lajili and Zéghal (2005)

145

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


98. A limited number of counterparties or group of closely related counterparties

IG18

LIQUIDITY RISK (Quantitative disclosure)

99. Summary quantitative data about exposure to LR at reporting date (gross market

risk exposure, average gross exposure and major types of market exposure)

7.34 Para 825

100. Gross finance lease obligations (before deducting finance charges) 7.B 14

101. Amount of concentration of LR with shared characteristics (i.e. geographical,

region or country)

7.34,7.B

8 , IG19

Para 825

102. Detailed breakdown: treasury bills, other bills, bonds, equity investments, other

investments

Para 825 Nier and Baumann (2006)

103. Coarse breakdown: Government securities, other listed securities, non-listed

securities


104. Investment securities or trading securities Para 825 Nier and Baumann (2006)

105. Deposits by type of customer; Bank deposits, municipal, government Para 825 Nier and Baumann (2006)

146

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


106. Long term funding; Convertible bonds, mortgage bonds, other bonds,

subordinated debt, hybrid capital


107. Maturity analysis of deposits; demand, savings (i.e., 3m, 3m-6m, 6m-1yr,1yr-

5yr, more than 5yr)


108. Total money market funding


Operational Risk (Qualitative disclosure)

109.A discussion of relevant internal and external factors considered in

measurement approach and scope and coverage of different approaches used

Para 825 Lajili and Zéghal (2005); Oliveira,

Rodrigues and Craig (2011)

110. A description of use of insurance for the purpose of mitigating operational risk Para 825 Lajili and Zéghal (2005); Oliveira,


111. Customer satisfaction Para 825 Lajili and Zéghal (2005); Oliveira,


112. Product development Para 825 Lajili and Zéghal (2005); Oliveira,


147

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


113. Efficiency and performance Para 825 Lajili and Zéghal (2005); Oliveira,


114. Environmental Para 825 Linsley and Shrives (2006)

115. Health and safety

Para 825

Equities Risk (Qualitative Disclosure) Para 825

116. Differentiation between holdings on which capital gains are expected and those

taken under other objectives, including for relationship or strategic reasons

Para 825

117. Discussion of important policies covering the valuation of and accounting for

equity holdings in the banking book

Para 825

Equities Risk (Quantitative Disclosure) Para 825

118. Fair value of investment and comparison to publicly quoted share values where

the share price is materially different

7.12 (1) Para 825

148

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


119. The type and nature of investments, including the amount, classified as publicly

traded and privately held

Para 825

120. The cumulative realised gain or loss arising from sales and liquidations at

reporting date

Para 825

121. Total unrealised gain or loss

Para 825

B. Capital Disclosure

122. Capital structure Para 825 Lajili and Zéghal (2005); Oliveira,


123. Amount of Tier 1 capital (including disclosure of paid up share capital,

reserves, minority interests, capital instruments, other amounts deducted from

goodwill and investments

Para 825 Lajili and Zéghal (2005); Oliveira,


124. Total amount of Tier 2 and Tier 3 capital Para 825 Lajili and Zéghal (2005); Oliveira,


125. Other deductions from capital Para 825 Lajili and Zéghal (2005); Oliveira,

149

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.



C. Internal corporate governance

126. Reporting frequency (yearly, quarterly, semi-annually) Para 825

127. Accounting policies ( income recognition, provisioning plan, valuation policy) Para 825 Uddin and Hassan (2011)

128. Ownership structure Para 825

129.Remuneration policies for directors and senior management Para 825

130. Audit fee breakdown Para 825

131. Interbank borrowing costs Para 825

132. Authority and responsibility assignment Para 825 Hernandez-Madrigal, Blanco-Dopico

and Aibar-Guzman (2012)

133.Access Para 825

134.Availability of information processing and technology Para 825

135.Infrastructure Para 825

150

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


D. Strategic Decision Risk Para 825

136.Strategic, operational, information and compliance objectives Para 825 Hernandez-Madrigal, Blanco-Dopico


137.Risk management philosophy Hernandez-Madrigal, Blanco-Dopico


138. Competition in product markets Para 825 Uddin and Hassan (2011)

139. Financial Performance measurement Para 825

140. Sovereign and political Para 825 Uddin and Hassan (2011); (Linsley &

Shrives 2006)

141. Permanent monitoring activities and independent assessments

Hernandez-Madrigal, Blanco-Dopico


E. General Risk Information

142. Relationship to Government development plan Abraham and Cox (2007); Beretta and

Bozzolan (2004); Cabedo and Miguel

151

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


Tirado (2004); Lajili and Zéghal

(2005); Uddin and Hassan (2011)

143. Customer acquisition process Abraham and Cox (2007); Beretta and



(2005); Linsley and Shrives (2006);

Uddin and Hassan (2011)

144. Recruitment of qualified and skilled professionals Abraham and Cox (2007); Beretta and





145. Natural disasters

Abraham and Cox (2007); Beretta and





152

Disclosure Items

IFRS 7

Ref.

Basel II

(Market

Discipline)

Ref.


F. Government Regulation Abraham and Cox (2007); Beretta and





146. Adverse changes in government regulation, control and taxation Abraham and Cox (2007); Beretta and





147. High degree of government regulation Abraham and Cox (2007); Beretta and





(1) Reclassification of Financial Assets (Amendments to IFRS 7) issued, effective 1 July 2008. (2) Improving Disclosures about Financial

Instruments (Amendments to IFRS 7) issued, effective for annual periods beginning on or after 1 January 2009.

153

6.6.2 Reliability of Risk Disclosure Index score

As mentioned earlier, the Risk Disclosure Index developed in this research is based on

two international standards (IFRS 7: Financial Instruments: Disclosures and Basel II:

Market Discipline). Two academics in accounting with financial reporting expertise and

five research associates acting as independent evaluators coded the data set to ensure the

reliability scale. Krippendroff (1980) considered it important that at least two

researchers do this type of analysis independently and compare results for reliability

checking.

The independent evaluators reviewed in the pilot study a total of 24 (11.42 per cent)

from the total of 210 annual reports. The researcher reviewed all 24 reports. The

unweighted Risk Disclosure Index coded by these independent evaluators was then

compared to ascertain if there were any statistically significant differences between

them. A t-test for differences in the means from each coders’ Risk Disclosure Index

(RDI) scoring was applied. The results are shown in Table 6.3.

Legend: N= 24; comparing the mean Risk Disclosure Index scores of both

researcher and evaluators.

Table 6.3 indicates the results are not statistically different (p>0.10) between the

researcher and the evaluators. This demonstrates a closeness in scoring between the

researcher and the evaluators in the pilot study. Hence, the scores for the Risk

Disclosure Index can be considered reliable.

11Table 6.3: Reliability tests of Risk Disclosure Index comparability

Mean t-tests Sig.(2 tailed)

Researcher 0.425 1.231 0.213

Evaluator 0.415

154

6.6.3 Sample design

This research conducts analysis using data from the period 2006 to 2012. There are

three reasons for choosing this period. First, this seven-year period provides a full

snapshot of risk reporting including a time dimension from pre-recession (2006),

recession (2007-2008) and post-recession (2009-2012). The study thus examines a

range of economic circumstances, from pre-recession (2006) to the post-recession

(2009-2012) period and the seven-year time frame provides valuable understandings of

the risk disclosure differentials in each period. Second, this study also investigates the

voluntary adoption status of IFRS 7 and Basel II: Market Discipline and in Bangladesh

over these periods. The seven-year period thus assesses whether the development of

international standards is associated with risk reporting. Therefore examining what is

effectively voluntary risk disclosure in annual reports provided over this time, due to the

nature of the institutional setting in Bangladesh, will make a contribution to the

literature. Third, the latest year, 2012, is the most recent period that enables reasonable

access to banks’ corporate reports.

6.6.4 Data collection

The study uses as its sample the population of all 30 listed banks on the Dhaka Stock

Exchange (DSE) in Bangladesh. The annual reports were downloaded from either the

Stock Exchange website or company websites. Unavailable reports were collected from

respective banks’ head offices, and the Bangladesh Securities and Exchange

Commission. Thus, 30 banks’ annual reports for years 2006 to 2012 were collected and

analysed, resulting in 210 observations. The annual reports from 2006-2008 are mostly

hand collected however, 2009 to 2012 reports were mostly available from banks’

websites. Thus, 210 annual reports were collected from November 2012 to June 2013.

6.6.5 The dependent variable

The Risk Disclosure Index score is used as the dependent variable in the analysis when

investigating the determinants of risk disclosure in Phase Two of the broader study. In

155

the third Phase of this study, testing of the association of risk disclosure with banks’

performance is conducted. Performance is measured using operating performance

(financial, employee efficiency, operating efficiency, deposit concentration) and bank

value (Tobin’s q and the book-to market ratio) aspects. Performance measures are the

dependent variables (separately) used to model the association of risk disclosure and

bank performance.

6.6.6 Independent and control variables

As discussed in Chapter 5, the underpinning theories for this study, institutional

isomorphism (i.e. coercive, mimetic and normative) and agency theory (board

independence, audit committee independence, risk committees) are measured as

independent variables in Phase Two (while investigating the underlying determinants of

risk disclosure). Additionally, board size, multinational linked audit firm, and age are

included as control variables. These factors are used commonly in the accounting risk

disclosure literature (Aebi, Sabato & Schmid 2012; Khan, Muttakin & Siddiqui 2012;

Lajili 2009; Linsley & Shrives 2006; Michael, Kaouthar & Daniel 2011; Oliveira,

Rodrigues & Craig 2011). In Phase Three, the lagged Risk Disclosure Index is used as

an independent variable with other control variables (board size, bank size, board

independence, GDP growth, inflation, leverage and lagged performance). For

convenience, the inclusion of all of these independent and control variables is justified

with the relevant regression models later in section 6.6.7.4.

6.6.7 Statistical data analysis techniques

This section presents the statistical data analysis technique employed in this research.

The statistical data analysis tools and techniques were selected as being appropriate to

the nature and objective of the study (Creswell & Clarke 2011). This thesis reports

descriptive statistics, other univariate statistics, bivariate correlations and multivariate

analyses. Stata version 13 and the Statistics Package for Social sciences (SPSS) version

21 were used for such analysis. Before proceeding with regression analysis, the

156

assumptions underlying (i.e. normality, multicollinearity) it were tested. The statistical

techniques used in this study are explained in detail in the following sub-sections.

6.6.7.1 Descriptive statistics

Descriptive statistics are used in this research to describe the Risk Disclosure Index and

other variables included in the testing of Hypotheses in detail. In particular, descriptive

analyses are provided to describe the five categories of risk disclosure (i.e. Liquidity,

Market, Operational, Equities and Credit) in terms of their individual component scores.

Descriptive statistics are used to represent the types of risk disclosure graphically, to

measure frequency distributions, central tendency and explore whether the assumptions

are met in relation to further statistical analysis.

6.6.7.2 Univariate statistics (Chi-Square tests, t tests, paired sample t tests, and

ANOVA)

Chi- Square tests are used in this thesis to determine first, whether differences in the

Risk Disclosure Index exist between big four and non-big four audited banks; and

second, whether differences in the Risk Disclosure Index exist between banks with or

without risk management units.

Independent sample t tests are used to compare the mean scores of two different groups

of conditions. The assumptions behind independent sample t tests are: a) the scores for

two groups are independent of each other, b) the scores for each group have equal

variances, and c) the distribution of the scores is normal.

The repeated measures paired sample t tests measure the changes in score at different

times. This thesis employs paired sample t tests to explore the significance of

differences in the score based on implemented international standards in respect of risk

disclosure across different periods.

157

Analysis of Variance (ANOVA) is a procedure to test the differences between two or

more population means and analyse the variance of the data to infer whether population

means differ (Hair et al. 2010). ANOVA involves comparing the mean score of more

than two groups. ANOVA employs one independent variable with a number of different

levels corresponding to different groups (Pallant 2010). As this study is conducted over

a seven-year period (2006-2012), ANOVA is used to compare the RDI over the period.

A large F ratio indicates more variability between the groups than within each group.

The significance of F indicates whether the null hypothesis can be rejected and the

population mean is equal.

6.6.7.3 Bivariate analysis (Correlation)

A series of correlations is conducted to explore the strength of the linear association

between two continuous variables. The effects of outliers, restriction of range and

multicollinearity concerns can be associated with coefficient correlations. The

coefficients take values from -1 to +1 (Hair et al. 2010; Pallant 2010).

Histograms, box plots, and z score values for each variable will be identified to check

for univariate outliers. Z score values exceeding a magnitude of 3.29 (p<0.001) will be

used to determine univariate outliers and the 5 per cent trimmed mean of variables will

be scrutinised to specify how much of a problem extreme values are likely to be (Pallant

2010).

Normality of variables is assessed by skewness and kurtosis. Skewness reflects the

symmetry of distribution and kurtosis refers to the peakiness of distribution (either too

peaked or too flat). The critical ratio from skewness and kurtosis indices provide an

assessment of univariate normality.

6.6.7.4 Multiple regression model

Multiple regression is performed to explore the predictive ability of a set of independent

variables on a continuous dependent variable. Multiple regression provides information

158

as a whole as to the contribution of each variable making up the model, whether

additional variables can contribute more predictability to the model, and whether control

variables enhance the predictive ability of the model.

The regression analysis used in second Phase of the study models the way in which the

possible explanatory variables explain the Risk Disclosure Index score. Additionally,

multivariate regression models are developed in the third Phase of the study to test the

association between the Risk Disclosure Index and bank performance. Thus, this thesis

employs Ordinary Least Squares (OLS) regression analysis models. A multivariate

regression model is developed to explain the simultaneous effects of the independent

and control variables on the dependent variable. The dataset in this study is a cross-

sectional time series or strongly balanced panel, however, the Hausman test statistics

failed to reject the null of no systematic differences in coefficients between pooled OLS

and panel fixed effects. Hence, the study estimated the regressions using the following

pooled OLS model. To determine the underlying determinants of the Risk Disclosure

Index, the study examined the following regression model in Phase Two.

+ + + + + +

+ YEARit + (Model 1)

Where, for Model 1, the dependent variable = is the corporate Risk Disclosure

Index score for bank i in year t and is estimated in the Phase One of the study using data

from annual reports. The independent and control variables in Model 1, are derived

from previous studies. Based on agency theory arguments, extant studies (Amran, Bin

& Mohd 2008; Beasley, Clune & Hermanson 2005; Oliveira, Rodrigues & Craig 2011)

have found an independent board to be a risk governance factor in explaining the extent

of risk disclosure. Consistent with previous studies, the researcher expects the

proportion of independent directors on the board, (board Independence for bank i in

year t), to have a positive relation with the Risk Disclosure Index. is measured as

159

the proportion of independent directors on the board. As discussed in Chapter 5, a

higher percentage of independent directors on the audit committee are more likely to

monitor the internal control risk management and risk reporting process more

effectively (Fraser & Henry 2007; Oliveira, Rodrigues & Craig 2011). Therefore, this

study expects a positive direction between the proportion of independent directors on

the audit committee, (audit committee independence for bank i in year t) and the

Risk Disclosure Index. is measured as proportion of independent directors on the

audit committee. Following Aebi, Sabato and Schmid (2012), it is expected that the

more a bank acknowledges its risk reporting concerns through establishing a larger

rather than smaller number of risk committees, (number of risk committees for

banki in yeart), the more likely it is to provide risk disclosures in its annual report. The

preference for effectiveness of risk committee measure (e.g. number of meeting) but this

being precluded by an absence of data. is measured as the total number of risk

committees established by a bank.

Model 1 includes the debt to equity ratio, , using debt to equity for bank i in year t.

Based on the coercive isomorphism concept, the more the bank depends on debt

financing, the more likely the creditors’ power is exercised in risk reporting (Barth &

Landsman 2010; Barth & McNichols 1994; Cormier, Gordon & Magnan 2004).

Following Abraham and Cox (2007); Aebi, Sabato and Schmid (2012); Oliveira,

Rodrigues and Craig (2011), Model 1 includes log transformed total assets,

(total assets for bank i in year t) based on the posited mimetic isomorphism Proposition

that mimetic isomorphism of larger banks has an influence on the degree of risk

reporting by smaller banks. As discussed in Chapter 5, normative isomorphism forces

professional influences and employee organisational practices such as, financial

reporting disclosure (Hassan 2009). Therefore, Model 1 includes the presence or

160

absence of a risk management unit35

, (risk management unit for bank i in year t,)

and it is expected that stronger risk communication in the annual reports of these banks

compared to banks that do not have a risk management unit.

Following Beltratti and Stulz (2012) and Aebi, Sabato and Schmid (2012), this study

also examines log transformed board size ( board size for banki in yeart,), the

presence of a multinational linked audit firm ( Multinational linked audit firm for

banki in yeart,) and log transformed age of bank ( Age of bank i in year t,) as control

variables. These control variables are consistently used in extant information disclosure

studies. For example, board size in Aebi, Sabato and Schmid (2012); Beltratti and Stulz

(2012)), multinational linked audit firm in Kleffner, Lee and McGannon (2003); Wang,

Zhu and Shen (2009) and age of business in Hill and Short (2009). Moreover, referring

to Chapter 4, Abraham and Cox (2007) found risk disclosure is negatively associated

with share ownership. The present study omits this variable in the regression model

because of the lack of data in the sample companies’ annual reports.

Table 6.4 defines the variable measurement in detail

35

Risk Management Unit is not included amongst the 147 items in the Risk Disclosure Index

161

Dependent Variable

Construct Variable Code Hypothesis Expected

sign

Measurement Type of

data

Source*

Risk Disclosure

Area

Risk Disclosure

Index

RDI H1 Risk Disclosure Index score for

bank (b) in year (y)

Continuous 3

Independent variables

Agency Theory Board Independence BI H2 + Proportion of independent

directors on the board

Continuous 1

Audit Committee

Independence

ACI H3 + Proportion of independent

directors on the audit committee

Continuous 1

Number of Risk

Committees

RC H4 + Total number of risk committees Continuous 1

Institutional

Isomorphism

Leverage - Debt to

Equity ratio

DE H5 + Total debt divided by total equity Continuous 1

Size - Total Assets LnTA H6 + Natural logarithm of total assets Continuous 1

Risk Management

Unit presence

RMU H7 + Indicator variable, 1= Risk

Management Unit (RMU), 0= No

RMU

Categorical 1

Control Variables

Bank

Characteristics

Board Size LnBS + Log of number of directors on the

board

Continuous 1

Multinational linked

Audit Firm

ML + Indicator variable, 1= if big four

auditor, 0= if non big four auditor

Categorical 1

Age LnAG + Log number of years from

incorporation

Continuous 1

*1=Annual Reports, 2= Bangladesh Securities and Exchange Commission, 3= Author Constructed measure = Stochastic error term

12Table 6.4: Variable definitions (Model 1)

162

As discussed in earlier sections, the third Phase of this study investigates whether any

potential association exists in relation to risk disclosure and banks’ performance.

Therefore, Chapter 5 of this study discusses the Hypotheses in relation to the

association of risk disclosure with bank performance. Bank performance is measured

using two broad aspects; bank operating performance (such as, financial performance,

employee efficiency, solvency efficiency, deposit concentration) and bank valuation

(hereafter, bank market performance). Bank market performance is measured using

Tobin’s q and the book to market ratio. The empirical model used in this study is based

on previous literature relating to information disclosure and performance.

Models 2-5 Bank operating performance = (Risk Disclosure Index score, Control

variables)

+ + + + + + +

+ + + + +

Year it + it (Models 2-5)

Models 6-7: Bank market performance = (Risk Disclosure Index score, Control

variables)

= + + + + + + +

+ Year it + it (Models 6-7)

Where OPERF (Operating Performance) represents the respective dependent variable

performance measures. For Models 2-5, the dependent variables modelled are financial

performance (ROA), employee efficiency (EEF), solvency efficiency (SEF) and deposit

concentration (DP) respectively. For Models 6 and 7, MPERF (Bank market

performance ) represents bank valuation; the dependent variables modelled are Tobin’s

q (TOBQ) and book to market (BTM).

163

In general, prior research uses return on assets (ROA) as the financial measure of

profitability. ROA reflects the ability of banks’ management to generate profit from

assets. Following Aebi, Sabato and Schmid (2012) and Hwang et al. (2009), this study

uses ROA as a proxy for measuring financial performance. The Employee efficiency

(EEF) measure quantifies the degree to which a banking organisation has grown in

capacity due to increased learning. This study follows Wang (2005) in measuring

employee efficiency, calculated as the natural logarithm of total operating income

divided by the number of employees. Solvency efficiency (SEF) is measured as capital

divided by total assets (Demirgüç-Kunt, Detragiache & Tressel 2008).

In measuring bank market performance, extant studies use Tobin’s q and the book-to

market ratio (Caprio, Laeven & Levine 2007; La Porta, Lopez-De-Silanes & Shleifer

1999). This study follows prior studies in controlling for specific factors deemed

significant in explaining variation in bank performance. For example, Aebi, Sabato and

Schmid (2012), Levine (2004) and Laeven and Levine (2009) found a significant

positive relation between bank governance factors (board size, board independence) and

bank operating and market performance. Additionally, bank specific characteristics,

such as bank size, is an important determinant of bank performance due to increasing

returns to scale in banking (Demirgüç-Kunt, Detragiache & Tressel 2008). The present

study controls for bank size by using the natural logarithm of total assets (Ben Naceur &

Kandil 2009; Demirgüç-Kunt, Detragiache & Tressel 2008) and expects its coefficient

to have a positive sign. Leverage is controlled for in this study following La Porta,

Lopez-De-Silanes and Shleifer (1999). They found leverage is negatively associated

with firm value.

This study also controls for GDP growth, considering that banks would benefit from

upward economic activity level. The economy in Bangladesh suffered from relatively

high inflation over the study period, which might have negative effect on bank

performance. Therefore, this study controls for the annual Consumer Price Index

(announced by the Ministry of Finance, Bangladesh) and expects a negative relation

with bank performance. Berger et al. (2005) argue that banks’ profitability has a

tendency to persist over time due to macroeconomic factors, market competition and/or

164

informational opacity. Therefore, operating performance models (2-5) in this study

control for lagged variables (LAG_ROA, LAG_EEF, LAG_SEF, LAG_DP). Table 6.5

defines the performance variable measurement in detail.

165

Dependent Variables

Construct Variable Code Hypothesis Measurement Type of data Source

Organisational

performance in different

aspects

Employee

Efficiency

EEF H8 Profit per employee (EEF) is measured as log of

(operating income/ no. of employee)

Continuous 1

Solvency

Efficiency

SEF H9 Solvency efficiency (SEF) is capital divided by total

asset

Continuous 1

Deposit

Concentration

DP H10 Deposit (DP) is measured as bank deposits divided

total deposits of all banks

Continuous 1

Financial

Performance

ROA H11 Return on asset (ROA) is calculated as net profit after

tax divided by total assets.

Continuous 1

Bank market

performance

TOBQ H12 Total assets – book value of equity + market value of

equity

Continuous 1

BTM Book value of assets divided by market value of

assets

Continuous 1


Risk Disclosure Index Lag_RDI Prior year Risk Disclosure Index score 2

Control Variables

Bank Characteristics

LnBS Log of number of directors on the board 1

SIZE Natural logarithm of total assets 1

BI Proportion of independent directors on the board 1

LEV Total debt divided by total equity 1

Macroeconomic Factors

GDPGR GDP growth (official annual real GDP growth Figures in per cent) 3

CPI Official annual Consumer Price Index in per cent 3

Lagged Performance measures

Lag_ROA Prior year return on assets 1

Lag_EEF Prior year profit per employee 1

Lag_SEF Prior year capital adequacy ratio 1

Lag_DP Prior year bank deposits divided total deposits of all banks 1

*1=Annual Reports, 2= Author Constructed measure, 3= Ministry of Finance, Bangladesh (2013); = Stochastic error term

13Table 6.5: Variable definitions (Models 2-7)

166

6.6.8 Sensitivity and supplemental analysis

Sensitivity analyses are reported in Chapter 10 in order to provide further explanation of

variables and explore the rigour of the major findings. The sensitivity analyses provide

additional insights into the dependent variables. This study examines different proxy

measures for variables to measure whether these change the statistical analyses.

Alternative proxies are used for institutional isomorphism (mimetic isomorphism

measured as Return on Assets (ROA), coercive isomorphism measured as total assets to

total deposits) and corporate governance (board independence remeasured as the

number of board meetings) constructs.

Supplemental analysis is reported in Chapter 11 to explore the association of five

categories of risk disclosure (Liquidity, Market, Operational, Equities and Credit) with

bank performance. Analysis of these categories is expected to provide further insights

into risk disclosure phenomena. Additional multivariate regression modelling in

Chapter 10 examines the association between the change in Risk Disclosure Index and

the change in predictor variables between sample sub-periods.

The regression model is as follows and Table 6.5 presents the variable definitions.

+ + + +

+ + + +

+ +

167

s (Change in variables)

Variables Code Measurement

Dependent variable

Change in Risk disclosure Index for bank

i year t and t-i,


Change in Board Independence

(proportion of independent directors) for

bank i in year t,

Change in Audit committee

independence (proportion of independent

members) for bank i in year t,

Change in Number of risk committees

for bank i between year t and t-i,

Change in Debt to equity ratio for bank i

between year t and t-i,

Change in Log of Total Assets for bank i

in year t,

Change in Indicator for Risk

Management Unit for bank i in year t,

Control variables

Change in Log of Board Size for bank i

in year t,

Change in Indicator for multinational

linked audit firm for bank i in year t,

Change in Log of Age of bank since

incorporation i in year t,

Stochastic error

6.7 The qualitative method

The aim of qualitative research includes gaining an understanding about the

significance, the consequences, or the outcome in diversified thinking of the context

(Bryman 2012; Wertz et al. 2011). Qualitative research allows the researcher to narrow

down the broad outline of the research concept with different social contexts entering

into the respondent’s perspective (Bryman 2012; Patton 2002). Therefore, qualitative

research yields a holistic overview and deep understanding of the insights of the

phenomena with direct communication between experts and related respondents.

Qualitative research in this study is used to validate the quantitative results from

secondary data providing deep understanding of the Risk Disclosure Index’s antecedent

factors and the effects thereafter by risk management and risk reporting experts.

Statistical techniques are used to analyse the quantitative data, in addition, qualitative

14Table 6.6: Variable definition

168

knowledge about the subject matter and its real world complexity provides the

necessary foundation and complement to quantitative research (Wertz et al. 2011). Thus

the interview technique used in this research provides practical information from those

at the ‘coalface’ and allows sharing of the experiences of experts (Bryman 2012;

Creswell & Clarke 2011). However, one limitation of qualitative research is that

interviewers may introduce bias into the data. Therefore, this research is conducted

using a mixed method approach to overcome the limitations of a single method

(quantitative or qualitative). The following sections illustrate the sampling technique,

interview design, data collection and analysis procedure for the qualitative analysis.

6.7.1 Justification of sampling procedure

The key informant approach was employed to obtain reliable interview data for this

study. This approach considers the ‘key participants’ from amongst knowledgeable

respondents about the research concern. Fourteen (14) interviews were conducted in

total.

The respondents were selected from amongst chief risk officers in risk management

units of listed banks, risk reporting managers from listed banks (where Risk

Management Units were not available), experts from the Bangladesh Securities and

Exchange Commission and experts in the policy development department from

Bangladesh Bank. The sample bank representatives were selected from these

organisations based on their availability.

The chief risk officer or the responsible head from the risk management unit was chosen

to be invited for interview. The invited interviewees were chosen both from

conventional (Non-Islamic) and non-conventional (Islamic) banking institutions to

better understand whether differences exist in their banking practices in relation to the

research topic in this study. The experts from the Bangladesh Securities and Exchange

Commission were chosen to approach for interviews as they monitor the capital market.

The experts from Bangladesh Bank were chosen to be invited, as they are involved

directly in developing risk management guidelines for banks.

169

6.7.2 Designing the interview protocol

Semi-structured questions were designed for the conduct of interviews in this study. The

interviews focused on the respondents’ opinions. Additionally, the researcher was able

to clarify respondents’ understandings about the interview questions since vague or

inadequate responses were able to be probed (e.g. ‘could you explain in detail?’) to

understand perspectives and experiences. Thus the researcher was able to control the

context of the interviews, exploring the range of complexity and depth of information

and potential sensitive issues (Bryman 2012).

In order to understand the level of risk disclosure, respondents were first asked to

discuss the current level of risk disclosure practices in the banking sector in Bangladesh.

The respondents were asked then to clarify (in their opinion) the underlying factors of

Risk Disclosure Index and the association of risk disclosure with bank performance.

Pre-testing the questions with four senior managers enabled assessment of the validity

of the questions in terms of the research objectives and revealed the time needed,

ranging from 45 to 60 minutes, for each interview. The researcher’s interview skills

were developed during this pre-testing phase of the interview process (Patton 2002;

Veal 2005).

6.7.3 Designing the interview protocol

The interview protocol was designed in two sections. In section A, four questions were

designed to understand the background information of respondents relating to

demographic (e.g. age, gender), educational and expertise level relating to this study.

Section B was designed to explore the dimensions of risk disclosure and the perceived

effect on performance from the various interviewees’ perspectives. Eight questions were

included in section B. Appendix 6.4 presents the interview protocol.

170

6.7.4 Data collection technique

To collect the qualitative data, the researcher initially contacted, using email and

telephone, the Bangladesh Securities and Exchange Commission, the research division

of the Bangladesh Bank and the risk management and reporting units of different listed

banks. The correspondence addresses were recorded from the Yellow Pages and

websites. The participants were contacted via telephone to arrange an interview

schedule. Interview times were selected based on the preference of interviewees and the

venue was either a meeting room in the organisation or the participants’ workstations. A

consent information statement and consent form were provided before the interview

took place. All respondents were guaranteed confidentiality and the interviewees were

asked to sign the consent form prior to interview. Participation was on a voluntary basis.

Interviewees agreed to be recorded in all cases and the researcher’s written notes added

further clarification of the interviewees’ responses. Each interview was given a random

code and only the researcher knows the name or organisation of the interviewee. The

signed consent forms are stored separately from the interview transcripts. Any list

connecting codes with names is not stored together. In the write-up stage of the thesis

where interviews and evidence of identity are used, neither participants nor their

organisations are identified. Code pseudonyms are used where direct quotes are reported

and other identifiable information is removed when reporting results.

The study protocol was maintained strictly through recording interviews, signing of

consent forms, writing hand notes and maintaining a register of dates of interview for all

interviews. A project overview was developed and revised continuously throughout the

data collection stage. Thus reliability was enhanced through maintaining the study’s

protocol and database (Yin 2009). Additionally construct validity is ensured through

multiple and different sources of information (recorded interviews, written notes and

secondary data) to form themes or categories for study (Creswell & Clarke 2011).

171

6.7.5 Data analysis

The most prevalent approach in qualitative research is narrative analysis involving

exploration of underlying themes (Bryman 2012; Tashakkori & Teddlie 2010).

Narrative analysis is a process of extracting qualitative information from narrated

experience in a systematic and objective approach with hermeneutic analysis of

meaning. According to Wertz et al. (2011) the narrative analysis approach can be

described as:

..Grounded in hermeneutics, phenomenology, ethnography, and literary analysis,

narrative research eschews methodological orthodoxy in favour of doing what is

necessary to capture the lived experience of people in terms of their own meaning

making and to theorize about it in insightful ways (p.225).

This study employs narrative analysis using in-depth interviews. Content analysis is a

common technique to interpret text interviews and reveal the structural forms

emphasising the content and its meaning (Hair 2007; Wertz et al. 2011). The interviews

were analysed thematically to understand the context of research problem. According to

Hair (2007), through systematic analysis the researcher examines the frequency of

words and main themes that occur and identifies the information content. Themes were

identified through similarities, dissimilarities, and recurrent words (Denzen & Linkon

1994).

The data analysis process begins with transcribing interviews and field notes. After

carefully reviewing the transcription, the researcher categorises the themes that were

established in the quantitative research relating to the Hypotheses. This procedure was

conducted within cases and between cases. Similar themes were drawn from different

interviews and then categorised as research constructs.

Beyond identifying the common patterns in quantitative and qualitative research,

additionally this study discusses the findings from interviews. Additional findings from

the qualitative research are discussed in Chapter 8 in detail.

172

The qualitative data analysis technique employed in this study is depicted in Figure 6.6.

Source: Creswell and Clarke (2011).

6.7.6 Reliability and validity

Achievement of reliability and validity are the strengths of qualitative research. The

validation process occurs throughout the steps presented in Figure 6.6 above. The

validity of qualitative findings in this study is ensured by triangulating quantitative

findings. Multiple strategies enhance research findings more accurately and build a

coherent justification (Creswell & Clarke 2011). The detailed descriptions by

interviewees provide realistic and richer understanding and different perspectives about

the research issue than would be possible with quantitative techniques alone. The

transcripts were sent to interviewees to ensure the reliability of transcription. During the

transcription process, the researcher communicated with the interviewees ensuring

reliability of the transcription process.

23 Figure 6.6: Qualitative data analysis technique

Raw data (audio tape, transcripts,

field notes)

Organising and preparing data

for analysis

Validating the

accuracy of

information

Interpreting the meaning of

theme

Interrelated themes

Themes

Reading through all data

173

6.8. Ethical clearance

Ethical issues were anticipated while conducting interviews in this study. The project

meets the requirement of ‘National Statement on Ethical Conduct in Human Research

(2007)’ by ‘Human Research Ethics Committee, Swinburne University of Technology’

with approval number 2012/270. The confidentiality conditions were explained to each

interviewee at the beginning of the interview process and the consent form was signed

(refer Appendix 6.5). As mentioned earlier, respondents were assigned a pseudonym

and their comments were described in general terms in the thesis. Data are stored in a

locked cabinet. The electronic data are stored on a password protected computer and

portable hard drive with access granted only to the researcher and the research

supervisors. This process was followed in accordance with Swinburne University’s

Code of Research Practices.


This Chapter justifies and provides a detailed outline of the research design consistent

with the methodological assumptions, outlines the use of methods in accordance with

these assumptions, describes the population, samples and various approaches used in

this study. This Chapter also describes the mixed method approach employed in this

study to attain the research objectives. Both qualitative and quantitative data collection

and analysis techniques are outlined in detail. The quantitative data are to be analysed

using content analysis and statistical techniques also. In addition, content analysis is to

be used for qualitative data. Thus, the mixed approach allows the researcher to achieve

the research objectives in more detail than a single approach. The Chapter concludes

with explanation of the privacy issues relevant to the interview respondents. The results

of qualitative and quantitative approaches are presented in the next five Chapters of this

thesis.

174

PART FOUR

ANALYSIS

Chapter 7: Corporate Risk Disclosure Practices in Bangladesh: Content

Analysis of Annual Reports

Chapter 8: An Exploration of the Risk Disclosure Practices and their

Determinants by Banks in Bangladesh: Qualitative Analysis of

Interview Data

Chapter 9: Factors Underlying Risk Disclosure: Descriptive, Univariate and

Bivariate Analysis

Chapter 10: Factors Underlying Risk Disclosure: Multivariate Statistics

Chapter 11: The Association between Risk Disclosure and Bank

Performance

175

Part Four provides a detailed analysis of the results from both quantitative and

qualitative data. Chapter 7 presents Phase One results of the broader study by

investigating the extent of risk disclosure that banking companies in Bangladesh make

as compared with the Risk Disclosure Index. This Chapter employs a content analysis

research method (using annual reports as the source) to investigate risk disclosure

practices.

Chapters 8, 9, and 10 provide Phase Two results of the broader study by investigating

the relationship between the Risk Disclosure Index and bank specific characteristics

such as board independence, audit committee independence, the number of risk

committees, debt to equity ratio, total assets, and the presence of a risk management

unit. Chapter 8 aims to explore the perceptions of interview participants’ in relation to

corporate risk disclosure practices and their determinants. This study provides

qualitative data from in-depth interviews with senior executives of the Bangladesh

Securities and Exchange Commission, the Bangladesh Bank (Central Bank) and risk

management and reporting units from different listed banks within the sample for this

study. The interview questions were semi-structured and were guided primarily by the

research objectives. Appropriate statistical tests are performed to assist in understanding

these relationships in Chapters 9 and 10. Chapter 9 seeks to examine the Hypothesised

relationships on a univariate basis, whilst Chapter 10 reports the multivariate testing of

Hypotheses (developed in Chapter 5).

Chapter 11 presents Phase Three of the broader study that aims to examine the

association between risk disclosure and bank performance. In the present research, bank

performance is measured using two broad aspects: bank operating performance and

bank market performance. Bank operating performance is measured as financial

performance, employee efficiency, solvency efficiency, deposit concentration and bank

market performance is measured using Tobin’s q and the book to market ratio. This

Chapter adopts an econometric approach to test the Hypothesised relationships for 30

listed banks in Bangladesh across the period 2006-2012. In this Chapter, both bivariate

and multivariate analyses are performed to test the research Hypotheses (developed in

Chapter 5)

176

CHAPTER 7: Corporate Risk Disclosure Practices in Bangladesh-

Content Analysis of Annual Reports

7.1 Introduction

This Chapter presents results from Phase One of the broader study that aims to

investigate corporate risk disclosure practices evidenced in annual reports of listed

Bangladesh banking companies’ from an international standards’ best practice

perspective. The purpose of the present Chapter is to investigate the extent of risk

disclosure that listed banking companies in Bangladesh make in relation to corporate

risk disclosure practices compared with the Risk Disclosure Index developed in Chapter

6. The Risk Disclosure Index is applied to investigate the risk disclosures of all 30 listed

banks in Bangladesh. This Phase of the research investigates whether the sample banks

provide publicly available information about the existence or non-existence of particular

best practices under international standards as captured in the Risk Disclosure Index.

Failure to provide such information publicly may impede the ability of stakeholders to

assess the risks of investing in or depositing with the respective organisations.

The findings reported in this Phase provide background for further research in later

Phases that addresses issues such as investigation of the underlying factors explaining

risk disclosure. International standards on and corporate responses to risk disclosure

requirements have evolved over the years that comprise the period of analysis (2006-

2012) involved in this Phase. Earlier in Chapter 2, it was proposed that given increasing

stakeholder concern relating to risk reporting, it is expected that across the period of

investigation (2006-2012) there will be evidence of increasing disclosure pertaining to

risk as per Hypothesis 136

.

The Risk Disclosure Index score obtained from analysis in this Chapter is used in

Chapters 9 and 10 to test empirically the relationship between banks’ risk disclosure and

36

H1: There are significant differences in risk disclosure over the period under examination (2006-2012).

177

its underlying determinants and in Chapter 11 to test between the extent of risk

disclosure and bank performance.

This Chapter is structured as follows. First, the Chapter presents the results after

examining risk disclosure practices and establishes the overall trends in risk disclosure

over the seven-year period. Then the results for categories of disclosure are presented.

Next, descriptive statistics summarise the sample observations and univariate statistics

are used to analyse any difference in risk disclosure across the different targeted time-

periods and any differences in risk disclosure between conventional (Non-Islamic) and

non-conventional (Islamic) banks. Subsequently, the results are discussed and

commented upon. A summary of the Chapter is given in the final section. Figure 7.1

provides an overview of this Chapter.

7.2 Trends in total corporate risk disclosure

Table 7.1 presents the trends in average Risk Disclosure Index score across the period

2006-2012. The Table shows the mean Risk Disclosure Index as a percentage of the

maximum possible 147 items for pooled (210 observations) and each year’s (30 banks)

data. The findings show that at the beginning of the period of analysis, sample banks

made minimal risk disclosure within their annual reports. In general, banks’ mean risk

disclosure has increased across time, supporting Hypothesis 137

.

37



Introduction (7.1) Trends in total risk

disclosure (7.2) Descriptive statistics

(7.3)

Univariate

analysis (7.4)

Discussion of

results (7.5) Chapter conclusion

(7.6)

178

Table 7.1 shows the growing trend in mean risk disclosure. The average risk disclosure

index score increased steadily across the period (2006-2012), rising from 43 per cent in

2006, to 50 per cent in 2007, to 53 per cent in 2008, to 62 per cent in 2009, to 71 per

cent in 2010, to 76 per cent in 2011 and 77 per cent in 2012. This analysis provides

evidence that there is an increasing trend in the mean risk disclosures reported by

sample banks in their annual reports over the seven-year period from 2006-2012,

supporting the growing importance of such disclosure and Hypothesis 138

.

The changing level of corporate risk disclosure is consistent with the increasing

relevance of risk reporting to various stakeholders and the implementation by

government and industry of various risk reporting initiatives, all of which increased

across the period of analysis. As predicted, the results provide clear evidence of the

impact of international standards (IFRS 7 and Basel II: Market Discipline) changes and

developments that lead sample banks to respond with an increased number of risk

information items disclosed in their annual reports in what is an effectively voluntary

disclosure setting. Table 7.2 presents the average Risk Disclosure Index score across the

various risk elements. This Table is analysed in the following sections.

38


15Table 7.1: Average Risk Disclosure Index (RDI) score, in each year (N=30) and pooled

(N=210)

Numbers represent % of Mean RDI with 147 (maximum possible score) as

denominator

Year Pooled (N=210)

2006 (N=30)

2007 (N=30)

2008 (N=30)

2009 (N=30)

2010 (N=30)

2011 (N=30)

2012 (N=30)

Mean

RDI

62 43 50 53 62 71 76 77

179

Risk Disclosure Items

Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

MARKET RISK (Qualitative disclosure)

Exposures to market risk (MR) and how they arise 73 40 60 63 83 86 88 90 Rises

Structure and risk management function(s) MR 62 20 43 43 60 87 90 93 Rises

Scope and nature of the entity's risk reporting or measurement systems of MR 66 35 50 47 63 87 90 93 Varies

MR policies for hedging and mitigating risk, including policies and procedures for

taking collateral 61 30 47 43 57 77 87 90

Varies

MR processes for monitoring the continuing effectiveness of hedges and mitigating

devices 63 30 43 40 60 80 91 93

Varies

Methods used to measure MR 53 12 27 27 50 77 87 90 Rises

MR policies and processes for on-and off-balance sheet netting 53 18 30 37 47 73 80 83 Rises

Interest income and expense for MR 51 12 27 37 50 73 79 80 Rises

MR maturity analysis of loans (i.e., 3months(m), 3m-6m, 6m-1yr,1yr-5yr, more

than 5yr) 60 40 93 97 100 100 100 100

Rises

MR maturity analysis of deposits; demand, savings(i.e., 3m, 3m-6m, 6m-1yr,1yr- 60 40 97 100 100 100 100 100 Rises

16Table 7.2: Mean Risk Disclosure Index score (per cent of max. possible [147]) by Index Item annually (N=30) and pooled (N=210)

180


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

5yr, more than 5yr)

Sensitivity analysis for currency risk 56 21 33 43 57 77 80 83 Rises

Sensitivity analysis for others’ price risk 31 12 10 17 27 47 50 53 Varies

Method and assumption used in sensitivity analysis 34 11 20 13 40 43 51 57 Rises

Explanation of method used in preparing sensitivity analysis 24 9 17 13 17 27 40 43 Varies

Main parameters and assumptions underlying the data provided 27 1 7 13 27 40 51 50 Rises

Explanation of the objective of the method and parameters used 22 1 7 10 17 33 40 43 Rises

Terms and conditions of financial instruments 38 6 20 27 47 50 53 63 Rises

The effect on profit or loss if the terms or conditions were met 21 6 13 13 23 23 30 40 Rises

A description of how the risk is hedged 32 11 20 20 33 40 46 57 Rises

Information about trading financial and non-trading financial instruments 81 56 77 80 90 87 87 90 Rises

Economic environment (hyperinflation or low inflation) 81 56 70 80 87 90 91 93 Rises

Foreign exchange rates 68 35 47 50 77 83 91 90 Rises

Prices of equity instruments 49 12 23 27 40 77 82 83 Rises

Market prices of commodities 36 5 13 17 30 57 57 70 Rises

181


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Prevailing market interest rate 37 12 23 23 27 50 60 63 Rises

Currency rates and interest rates for foreign currency financial instruments such as

foreign currency bonds 39 11 27 27 40 60 53 57

Rises

A description of how management determines concentrations 49 13 37 37 47 63 71 73 Rises

If concentrated in one or more Industry sector (such as retail or wholesale) 47 26 87 90 90 97 97 97 Rises

If an entity concentrated on one or more credit quality (such as secured and

unsecured loans) and (investment grade or speculative grade) 59 26 57 60 63 67 67 70

Rises

Geographical distribution (such as Asia or Europe) 85 36 87 90 90 97 98 97 Varies

A limited number of counterparties or group of closely related counterparties 46 12 27 27 40 67 71 77 Varies

Key assumptions regarding loan prepayments and behaviour of no maturity deposits 27 2 10 10 17 43 53 57 Rises

Long term funding; convertible bonds, mortgage bonds, other bonds, subordinated

debt, hybrid capital 45 16 80 80 87 93 91 90

Varies

Total money market funding 71 36 67 70 80 87 79 80 Varies

MARKET RISK (Quantitative disclosure)

Summary quantitative data about exposure to MR at the reporting date (gross

market risk exposure, average gross exposure and major types of market exposure) 46 0 13 17 37 73 91 93

Rises

182


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Sensitivity analysis for interest risk 37 0 10 13 30 60 71 73 Rises

Sensitivity analysis for currency risk 37 2 17 20 37 60 61 63 Rises

Sensitivity analysis for other price risk 23 6 3 7 13 37 42 50 Rises

Amount of concentration of MR with shared characteristics (i.e. geographical,

region or country) 75 34 73 77 80 87 87 90

Rises

CREDIT RISK (Qualitative disclosure)

Exposures to credit risk (CR) and how they arise 58 34 90 93 97 97 98 97 Varies

Structure and risk management function(s) 89 60 87 90 93 97 97 100 Rises

CR scope and nature of the entity's risk reporting or measurement systems 73 35 63 63 77 90 91 93 Rises

CR policies for hedging and mitigating risk, including policies and procedures for


Rises

Processes for monitoring the continuing effectiveness of hedges and mitigating

devices for CR 74 27 70 73 80 83 91 93

Rises

Methods used to measure CR 71 24 57 67 80 87 91 93 Rises

CR policies and processes for on-and off-balance sheet netting 66 35 50 53 67 83 87 87 Rises

183


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Loans by type (government, mortgage, lease, and other loans 56 36 87 90 97 97 93 97 Varies

Policies and processes for valuing and managing collateral and other credit

enhancements obtained 26 0 10 10 23 40 42 57

Rises

Description of main types of collateral and other credit enhancements 36 12 27 27 33 47 52 53 Rises

Main types of counterparties to collateral and other credit enhancements and their

creditworthiness 33 5 13 13 23 47 63 67

Rises

Information about CR concentrations within the collateral or other credit

enhancements 40 6 20 23 40 50 72 70

Rises

Nature and carrying amount of assets obtained by taking possession of collateral

held as security or called on other credit enhancements 41 7 30 27 47 50 63 63

Varies

Definitions of past due and impaired 23 9 0 3 7 40 50 50 Varies

The nature of the counter party 30 0 10 10 13 50 60 70 Rises

Any other information used to assess credit quality 24 0 0 10 13 43 50 53 Rises

Rating agencies used for external ratings when managing or monitoring credit

quality 69 34 70 73 70 73 79 80

Varies

A description of how management determines concentrations for CR 47 12 27 27 40 67 80 80 Rises

184


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

If concentrated in one or more Industry sector (such as retail or wholesale) 76 26 87 83 93 97 98 97 Varies

If an entity concentrated on one or more credit quality (such as secured and

unsecured loans) and (investment grade or speculative grade) 57 26 47 47 63 67 70 80

Varies

Geographical distribution of CR (Asia or Europe) 87 54 77 83 97 97 100 100 Rises

A limited number of counterparties or group of closely related counterparties of CR 45 12 27 30 47 50 70 80 Rises

The bank’s objectives in relation to securitisation activity, including the extent to

which these activities transfer CR of the underlying securitised exposures away

from the bank to other entities

54 14 37 40 73 67 72 77

Varies

Summary of accounting policies for securitisation activities, including: whether the

transactions are treated as sales or financings; recognition of gain on sale key

assumptions for valuing retained interests, including any significant changes since

the last reporting period and the impact of such changes

58 27 47 50 70 70 71 73

Rises

CREDIT RISK (Quantitative disclosure)

Summary quantitative data about exposure to CR at reporting date (gross credit risk

exposure, average gross exposure and major types of credit exposure) 54 13 33 40 57 73 76 87

Rises

Amount of maximum exposure to CR (before deducting value collateral) 46 8 17 27 47 67 71 87 Rises

Granting financial liabilities, grantees should be significantly greater than liability 30 12 27 27 30 40 36 37 Rises

185


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

For loan commitment (irrecoverable over the life of the facility or recoverable only

in response to a material adverse change) the maximum credit exposure is the full

amount of the commitment

31 0 3 13 27 53 57 67

Rises

Amount of concentration of CR with shared characteristics (i.e. geographical, region

or country) 79 34 67 73 87 93 100 100

Rises

By class of financial assets, an analysis of the age of financial assets that are past

due as at the reporting date but not impaired. For example, time brands may be not

more than 3m, 3m to 6m, 6m to 1yr; and more than 1yr.

38 14 23 27 33 53 55 60

Rises

Amount of credit exposures for each external credit grade 34 11 13 13 33 53 57 57 Rises

Amount of an entity's rated and unrated credit exposures 28 0 10 10 20 50 55 50 Rises

The total outstanding exposures securitised by the bank and subject to the

securitisation framework (broken down into traditional/synthetic), by exposure type 53 12 40 50 53 63 73 77

Rises

Aggregate amount of securitisation exposures retained or purchased, broken down

by exposure type 37 13 23 37 33 47 50 57

Varies

Loan loss reserves 26 7 17 23 30 33 38 37 Rises

Contingent liability 94 56 100 100 100 100 100 100 Rises

Off-balance sheet item 93 54 100 100 100 100 100 100 Rises

186


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Loan loss provision 80 50 80 80 83 90 88 89 Varies

Liquidity RISK (Qualitative disclosure)

Exposures to solvency risk (LR) and how they arise 74 35 70 73 77 83 87 89 Varies

Structure and risk management function(s), including a discussion of independence

and accountability for LR 74 53 67 70 73 80 85 87

Rises

Scope and nature of the entity's LR reporting or measurement systems 60 34 50 53 53 73 75 80 Rises

LR policies for hedging and mitigating risk, including policies and procedures for


Varies

LR processes for monitoring the continuing effectiveness of hedges and mitigating

devices 65 50 60 60 60 73 75 80

Rises

Methods used to measure LR 54 26 40 40 53 70 73 77 Rises

LR policies and processes for on-and off-balance sheet netting 51 23 43 40 47 67 70 70 Rises

judgement to determine an appropriate number of time bands (i.e. 0-1m, 1-3m, 3m-

1yr, 1yr-5yrs) 48 12 27 30 40 67 78 83

Rises

A maturity analysis of the expected maturity dates of both financial liabilities and

financial assets 69 36 50 57 70 87 88 97

Rises

187


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Undrawn loan commitments 49 26 40 43 50 53 63 63 Rises

Readily available financial assets in liquid market to meet solvency needs 43 13 27 33 37 57 67 67 Rises

Committed borrowing facilities (e.g., commercial paper) or other line of credit

(stand-by credit facility) 58 26 40 50 63 70 75 80

Rises

Financial assets for which there is no liquid market, but which are expected to

generate cash flows (principal or interest) 29 13 23 23 27 37 47 37

Varies

Deposits at central banks to meet solvency needs 71 46 73 73 73 73 75 80 Rises

Diverse funding sources 51 24 40 40 47 60 75 70 Varies

Significant concentrations of solvency risk (assets or funding source) 48 20 40 40 43 57 65 73 Rises

A description of how management determines concentrations of LR 47 17 33 40 43 60 65 70 Rises

If concentrated in one or more Industry sector (such as retail or wholesale) 86 56 80 80 93 97 98 97 Varies

If entity concentrated on one or more credit quality (such as secured and unsecured

loans) and (investment grade or speculative grade) 63 30 63 60 67 73 75 73

Varies

Geographical distribution of LR (Asia or Europe) 83 41 77 73 97 97 98 97 Varies

A limited number of counterparties or group of closely related counterparties 41 12 23 27 40 50 65 67 Rises

188


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Liquidity RISK (Quantitative disclosure)

Summary quantitative data about exposure to LR at reporting date (gross market

risk exposure, average gross exposure and major types of market exposure) 38 0 10 17 37 63 65 73

Rises

Gross finance lease obligations (before deducting finance charges) 33 12 27 30 33 40 44 47 Rises

Amount of concentration of LR with shared characteristics (i.e. geographical, region

or country) 80 53 77 80 87 90 86 87

Varies

Detailed breakdown: treasury bills, other bills, bonds, equity investments, other

investments 90 56 90 90 97 100 100 100

Varies

Coarse breakdown: Government securities, other listed securities, non-listed

securities 84 56 83 87 90 90 91 92

Rises

Investment securities or trading securities 91 57 93 93 97 100 100 100 Rises

Deposits by type of customer; Bank deposits, municipal, government 70 59 100 100 100 100 100 100 Steady

Long term funding; Convertible bonds, mortgage bonds, other bonds, subordinated

debt, hybrid capital 91 57 97 97 97 97 98 99

Varies

Maturity analysis of deposits; demand, savings (i.e., 3m, 3m-6m, 6m-1yr,1yr-5yr,

more than 5yr) 62 46 100 100 100 100 100 100

Steady

189


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Total money market funding 73 46 70 70 80 80 82 83 Rises

Operational Risk (Qualitative disclosure)

A discussion of relevant internal and external factors considered in measurement

approach and scope and coverage of different approaches used 78 36 67 70 87 93 98 97

Varies

A description of use of insurance for the purpose of mitigating operational risk 27 0 17 17 20 43 45 50 Rises

Customer satisfaction 74 35 53 63 83 93 96 97 Rises

Product development 72 36 57 63 80 87 90 93 Varies

Efficiency and performance 83 56 70 73 90 97 97 100 Rises

Environmental 73 23 53 63 87 93 95 93 Rises

Health and safety 66 23 43 50 73 87 87 100 Rises

Equities Risk (Qualitative Disclosure)

Differentiation between holdings on which capital gains are expected and those

taken under other objectives, including for relationship or strategic reasons 42 11 20 27 27 57 74 77

Rises

Discussion of important policies covering the valuation of and accounting for equity

holdings in the banking book 57 12 33 40 57 80 90 90

Rises

190


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Equities Risk (Quantitative Disclosure)

Fair value of investment and comparison to publicly quoted share values where the

share price is materially different 70 37 63 73 73 77 83 83

Rises

The type and nature of investments, including the amount, classified as publicly

traded and privately held 87 56 87 90 93 93 96 97

Rises

The cumulative realised gain or loss arising from sales and liquidations at reporting

date 44 12 37 40 40 53 57 67

Rises

Total unrealised gain or loss 39 11 27 33 33 53 57 60 Rises

Capital Disclosure

Capital structure 92 69 87 90 100 100 100 100 Rises

Amount of Tier 1 capital (including disclosure of paid up share capital, reserves,

minority interests, capital instruments, other amounts deducted from goodwill and

investments

48 5 87 90 100 100 100 100

Rises

Total amount of Tier 2 and Tier 3 capital 83 3 87 90 100 100 100 100 Rises

Other deductions from capital 35 5 23 30 33 43 55 56 Rises

Internal corporate governance

191


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Reporting frequency (yearly, quarterly, semi-annually) 98 83 100 100 100 100 100 100 Steady

Accounting policies ( income recognition, provisioning plan, valuation policy) 77 63 90 90 100 100 100 100 Rises

Ownership structure 56 35 90 90 100 100 100 100 Rises

Remuneration policies for directors and senior management 69 39 70 70 73 77 78 79 Varies

Audit fee breakdown 53 37 53 53 53 57 57 58 Rises

Interbank borrowing costs 55 36 60 53 53 57 60 63 Varies

Authority and responsibility assignment 85 50 83 83 93 93 95 97 Rises

Access 50 40 83 83 97 97 100 100 Rises

Availability of information processing and technology 58 46 83 83 97 97 100 100 Rises

Infrastructure 85 50 80 80 93 93 100 100 Rises

Strategic Decision Risk

Strategic, operational, information and compliance objectives 59 36 87 87 97 97 98 99 Rises

Risk management philosophy 42 26 73 77 90 90 98 99 Rises

Competition in product markets 79 43 67 70 90 93 94 95 Rises

Financial Performance measurement 84 50 73 80 93 97 97 97 Rises

192


Pooled

%

N=210

2006

%

N=30

2007

%

N=30

2008

%

N=30

2009

%

N=30

2010

%

N=30

2011

%

N=30

2012

%

N=30

Trend

Sovereign and political 36 12 27 33 43 43 46 47 Rises

Permanent monitoring activities and independent assessments 41 25 73 80 90 92 92 93 Rises

General Risk Information

Relationship to Government development plan 51 21 47 47 60 60 62 60 Varies

Customer acquisition process 62 26 57 57 73 73 74 75 Rises

Recruitment of qualified and skilled professionals 67 23 63 63 77 80 82 83 Rises

Natural disasters 52 36 50 50 63 53 57 58 Varies

Government Regulation

Adverse changes in government regulation, control and taxation 28 12 23 23 30 30 37 38 Varies

High degree of government regulation 50 25 47 50 57 57 57 58 Varies

193

7.2.1 Risk disclosure by key categories

Content analysis was further conducted to classify the data into sub-categories and gain

a sense of the types of risk information disclosed. The risk disclosure text was classified

and calculated into seven key categories as discussed in Chapter 6, namely i) Risk

Types (Market, Credit, Liquidity, Operational and Equities); ii) Capital Disclosure; iii)

Internal Corporate Governance; iv) Information and Communication risks; v) Strategic

Decision risks; vi) General Risk Information; and vii) Government Regulation. Table

7.3 presents the differences in Risk Disclosure Index score (in terms of average) for

these seven broad categories across the period 2006 to 2012.

Risk Disclosure Categories Pooled

N=210

2006

N=30

2007

N=30

2008

N=30

2009

N=30

2010

N=30

2011

N=30

2012

N=30

Risk Type 63 39 47 51 61 73 80 87

Capital Disclosure 79 60 71 75 83 85 88 90

Internal Corporate Governance 78 60 78 77 82 83 84 83

Information and Communication

risks 86 56 69 82 96 96 100 100

Strategic Decision risks 77 56 67 71 84 85 87 88

General Risk Information 64 52 68 54 68 67 68 70

Government Regulation 40 20 35 37 43 43 47 57

Legend: Numbers represent % of RDI with 147 (maximum possible score) as

denominator in each risk category

Table 7.3 shows an growing trend in disclosure for each of the seven broad categories

over the period. The mean percentage of risk item disclosures in each key risk category

shows a sharp increase. The Table reveals that there is an upward trend in Risk Types,

Capital Disclosure, Internal Corporate Governance, Strategic Decision risks and

Government Regulation categories. The Table shows that the average number of risk

disclosure items differs among the categories, and that there is more risk disclosure

17Table 7.3: Mean Risk Disclosure Index (RDI) score (%) by category annually (N=30) and

pooled (N=210)

194

made by banks in the Information and Communication categories in comparison to

other key categories. The minimum Risk Disclosure Index scores are in the Government

Regulation category (20 per cent in 2006 and 57 per cent in 2012). Table 7.3 further

reveals that Internal Corporate Governance and General Risk Information reduce in

2008; however these two categories increase gradually in subsequent years.

7.2.2 Risk disclosure by Risk Types

A breakdown of the data by Risk Type is described in this section. The broad Risk

Types consist of Market risk (MR), Credit risk (CR), Liquidity risk (LR), Operational

risk (OR) and Equities risk (ER) disclosures. Table 7.4 reveals the disclosure trends for

the five (MR, CR, LR, OR, ER) sub-categories under Risk Types.

Risk

Type

Year Trend

Pooled

N=210

2006

N=30

2007

N=30

2008

N=30

2009

N=30

2010

N=30

2011

N=30

2012

N=30

Market risk 56 32 39 41 53 68 76 83 Rises

Credit risk 59 36 43 47 57 68 76 84 Rises

Liquidity risk 68 51 57 59 65 75 80 87 Rises

Operational risk 70 38 51 57 74 85 90 93 Rises

Equities risk 60 38 44 51 54 69 79 87 Rises

Legend: Numbers represent % of Mean RDI with 147 (maximum possible score) as

denominator

Table 7.4 reveals the trend in the mean Risk Disclosure Index score items in each sub-

category is upward over the period from 2006-2012. The lowest mean scores for all

Risk Disclosure Index sub-categories are in 2006. The Table further reveals that mean

Market risk disclosure ranges from 32 to 83 per cent and Market risk disclosure is lower

18Table 7.4: Mean Risk Disclosure Index (RDI) score (%) by Risk Type

annually (N=30) and pooled (N=210)

195

compared to other categories based on the pooled data, followed by Credit risk, Equities

risk, Liquidity risk and Operational risk. Credit risk means range between 36-84 per

cent, Liquidity risk between 51-87 per cent, Operational risk between 38-93 per cent

and Equities risk between 38-87 per cent.

Table 7.4 further reveals a significant change in mean risk disclosure items in year

2010. The percentage growth rates, such as Market risk 16 per cent, Credit risk 11 per

cent, Liquidity risk 9 per cent and Equities risk 15 per cent (the numbers represent

changes between each year) is highest in 2010 for all categories except for operational

risk (highest 17 per cent in 2009) across the period. A further breakdown of disclosure

of Market, Credit, Liquidity, Operational and Equities risk is presented below according

to whether disclosures are qualitative or quantitative in nature.

7.2.3 Qualitative and quantitative disclosure

Table 7.5 show the qualitative (QL) and quantitative (QN) risk disclosure for each year

and pooled. Table 7.5 indicate the qualitative or quantitative nature of Market, Credit,

Liquidity, Operational and Equities mean Risk Disclosure Index scores across the

period (2006-2012). In terms of qualitative risk disclosure, Credit risk (23-79 per cent),

Market risks (19-76 per cent), Liquidity (20-77 per cent) are by far the highest sub-

categories of risk disclosed over time. Interestingly Equities risk disclosure is zero in

2006 while 83 per cent in 2012. The quantitative disclosure of Market risk ranges from

a mean of 9 per cent to 74 per cent, Credit risks range from 22 to 71 per cent, Liquidity

risk from 45 to 88 per cent, and Equities risk from 12 to 78 per cent.

196

Market risk Credit risk Liquidity risk Operational risk Equities risk

QL QN QL QN QL QN QL QN QL QN

Pooled (N=210)

54 44 58 52 57 77 68 0 48 60

2006 (N=30)

19 9 23 22 20 45 28 0 0 12

2007 (N=30)

41 77 46 40 49 75 51 0 27 62

2008 (N=30)

43 27 48 44 51 76 57 0 33 67

2009 (N=30)

41 77 46 40 49 75 51 0 27 62

2010 (N=30)

69 37 70 65 69 86 85 0 68 78

2011 (N=30)

76 74 79 71 76 88 90 0 83 78

2012 (N=30)

76 74 79 71 76 88 90 0 83 78

Legend: QL= Qualitative risk disclosure; QN= Quantitative risk disclosure. Numbers

represent % of Mean RDI with 147 (maximum possible score) as denominator.

The mean statistics for these disclosures reveal that the extent of each of qualitative and

quantitative disclosures is increasing each year. The lowest score for all risk disclosure

sub-categories is in 2006, the earliest year of GFC and the highest score is witnessed in

2012.

7.3 Descriptive statistics for the Risk Disclosure Index

This section presents the descriptive statistics for the seven key categories of the Risk

Disclosure Index. Table 7.6 presents descriptive statistics for the categorical risk

disclosures and Table 7.7 presents descriptive statistics for categories of risk disclosure

that are assessed individually in each category and aggregately in the total Risk

Disclosure Index.

19Table 7.5: Mean Qualitative and Quantitative Risk Disclosure Index

(RDI) score for each Risk Type annually (N=30) and

pooled (N=210)

197

Key Risk Categories N Min. Max. Mean Std. Deviation

Risk Type 210 25 117 77 24

Capital disclosure 210 0 4 3 1

Internal corporate governance 210 3 7 6 1

Information and communication risks 210 0 3 3 1

Strategic decision risks 210 0 6 5 1

General risk information 210 0 4 3 1

Government regulation 210 0 2 1 1

Legend: Numbers represent counts of actual disclosures

Table 7.6 shows descriptive statistics for the seven key categories of risk disclosure.

Each category represents a part of the total Risk Disclosure Index. The maximum risk

disclosure is in the Risk Types category (77 with 117 maximum) and the minimum risk

disclosure is in the Government Regulation category (2 with 0 minimum). As the Risk

Types category contains the maximum number of items, the average risk disclosures are

highest in the Risk Types. Further, it is necessary to mention that Table 7.6 represents

only the disclosed items in each category of Risk Disclosure Index.

The Table 7.7 presents the percentage of disclosed items in each category individually

(Risk Type [121 items], Capital Disclosure [4 items], Internal Corporate Governance [7

items], Information and Communication [3 items], Strategic Decision [6 items], General

Risks Information [4 items], Government Regulation [2 items]) and categorical

disclosures in the Risk Disclosure Index (147 items) aggregately. The Table shows the

maximum score is achieved in disclosures about Government Regulation and the

minimum score achieved in Risk Types. The Table indicates the highest score occurs in

the Information and Communication group (92) and the lowest average is in General

Risk Information disclosure (42). As the maximum number of items is contained in the

Risk Types group, columns 1 and 3 show the maximum disclosure is in the Risk Types

group.

20Table 7.6: Descriptive statistics for seven key categories of Risk Disclosure Index

198

N Min. Max. Mean Std.

Dev.

Risk Type in total Risk Type (121 items)

210 21 97 63 20

Risk Type (121 items) in Risk Disclosure Index

(147 items)

210 17 80 52 17

Capital Disclosure in total Capital Disclosure (4

items)

210 0 100 82 20

Capital Disclosure (4 items) in Risk Disclosure

Index (147 items)

210 0 0 0 0

Internal corporate governance in total Internal

corporate governance (7 items)

210 43 100 81 15

Internal corporate governance (7 items) in Risk

Disclosure Index (147 items)

210 0 0 0 0

Information and Communication in total

Information and Communication (3 items)

210 0 100 93 25

Information and Communication (3 items) in Risk


210 0 0 0 0

Strategic decision in total Strategic decision (6

items)

210 0 100 80 24

Strategic decision (6 items) in Risk Disclosure

Index (147 items)

210 0 0 0 0

General risk information in total General risk

information (4 items)

210 0 100 63 36

General risk information (4 items) in Risk


210 0 0 0 0

Government regulation in total Government

regulation (2 items)

210 0 100 42 38

Government regulation (2 items) in Risk


210 0 0 0 0

21Table 7.7: Descriptive statistics for seven key categories individually in each category

and aggregately in the total Risk Disclosure Index

199

The Table further reveals that the Risk Types dominates the other groupings within the

Risk Disclosure Index, as the highest number of items is included in this category. The

highest mean (52 with 80 maximum) is under the Risk Types group and the lowest is in

the Government Regulation (1 with 0 minimum) group.

7.4 Comparison of Risk Disclosure Index over the period: Univariate

analysis (t-tests and ANOVA)

An earlier section (section 7.2) of this Chapter shows that the mean overall Risk

Disclosure Index score as a percentage of the total possible items (147) increased from

43 per cent in 2006 to 77 per cent in 2012. This section examines statistically the

differences between disclosures over the seven-year period in order to test whether

significant differences exist in the level of risk disclosure across the period (2006-2012).

7.4.1 Significance of Risk Disclosure Index over the period: ANOVA

To compare the mean score from different periods (2006-2012), one-way analysis of

variance (ANOVA) is performed. Table 7.8 shows the mean Risk Disclosure Index

score by year ANOVA.

Year 2006 2007 2008 2009 2010 2011 2012 F Sig.(2-

tailed)

Mean 0.430 0.500 0.527 0.621 0.710 0.764 0.773 23.155 0.000

N 30 30 30 30 30 30 30

Table 7.8 highlights that the Risk Disclosure Index mean percentage increases in each

sample year and that there is a statistically significant difference at the p < .01 level in

the Index for the period from 2006-2012. Appendix 7.1 indicates analysis of post hoc

22Table 7.8: Risk Disclosure Index (%) by year ANOVA

200

Tukey statistics by year that reveals the level of the Risk Disclosure Index score is

significant mostly at the 5% level with some at the 10% level. The Tukey statistic also

suggests that the Risk Disclosure Index mean percentage is lower in 2006 to 2008

compared to that in 2009-2012.

7.4.2 Conventional (Non-Islamic) and non-conventional banks (Islamic)

Table 7.9 reports the average Risk Disclosure Index and their differences between

conventional (23 banks: 23*7=161) and non-conventional (7 banks: 7*7=49) banks.

Legend: RDI as a mean percentage score compared to maximum possible score (147)

*49 non-conventional banks represent 23% of total observations

Table 7.9 shows that conventional banks on average disclose more risk items compared

to their non-conventional counterparts and the differences are statistically significant.

The difference implies that shareholders of non-conventional banks do not demand of

their invested banks that they follow international disclosure standards or that non-

conventional banks prefer not to disclose their potential risk information, or a

combination of both.

23Table 7.9: Mean difference in Risk Disclosure Index (RDI) between conventional

and non-conventional (Islamic) banks (2006-2012)

Banks Mean RDI

Numbers represent % of Mean RDI

Conventional (n=161) 0.69

Non-conventional (n=49)* 0.56

Difference 0.13

t-statistic 4.25

p-value 0.000

201

7.4.3 Comparisons of pre- and post GFC periods

Both parametric tests (paired sample t-tests) and non-parametric (e.g., Wilcoxon signed-

rank tests) are conducted to test whether the differences among the years examined are

significant. In a global context, three different periods are observed in Table 7.9, the

GFC (2007-2008), transition (2009-2010) and post-GFC (2011-2012) periods.

Wilcoxon signed rank tests are designed for repeated measures. The Wilcoxon signed-

rank test is a non-parametric test and involves comparisons of differences between two

populations (Pallant 2010). Table 7.10 shows that there are significant differences in the

Risk Disclosure Index between years 2007-2008, 2009-2010 and 2011-2012. Thus, it

can be concluded that the three sets of risk disclosure scores are significantly different

from each other. The results are reported in Table 7.10.

Test Statisticsa

RDI_2007 - 2008 RDI_2009-2010 RDI_2011 -2012

Z -3.731b -4.465

b -4.796

b

Asymp. Sig. (2-tailed) .000 .000 .000

a. Wilcoxon Signed Rank Test

b. Based on negative ranks


The Wilcoxon Signed Rank Test in Table 7.10 reveals a statistically significant level of

risk disclosure in the three periods, Z= -3.73(2007-2008), -4.465 (2019-2010) and -

4.796 (2011-2012) with p <.001.

A paired sample t test was also performed to determine if there are any significant

differences between the mean percentage levels of Risk Disclosure Index score across

the periods. The results are presented in Table 7.11. The Table indicates results for the

24Table 7.10: Wilcoxon Signed Rank tests

202

paired sample t tests. There is a significant increase in mean Risk Disclosure Index

score from 2007-2008 to 2009-2010 by 6.16 with p <.001 (2 tailed).


Moreover, in comparison to 2009-2010 in 2011-2012 the Risk Disclosure Index

increases with a p value < 0.01. The Eta squared statistic (refer Appendix 7.2) indicates

a large effect size in each of the three periods. The largest effect occurs with a

substantial difference in Risk Disclosure Index score in the transitional period (2009-

2010).

Table 7.12 presents a paired sample t-test to examine if there is a significant difference

between the average level of risk disclosure in year 2006 (pre-GFC period) and year

2007 (GFC period). There is a significant increase in the mean percentage Risk

Disclosure Index score from 2006 to 2007 with p <.001 (2 tailed). The mean difference

in the two scores is 0.068, with a 95 per cent confidence interval stretching from a lower

bound of 0.05 to 0.09.

39

The guideline proposed by Cohen (1988, pp. 284-7) for interpreting the values is .01= small effect,

.06= moderate effect, .14= large effect

25Table: 7.11 Paired sample t tests of mean RDI (%) across discrete periods

Period Mean t df Sig.(2-

tailed)

Eta

squared

Effect 39

RDI_2007 –

RDI_2008

0.027 2.706 29 .011 0.201 Large

effect

RDI_2009–

RDI_2010

0.088 5.732 29 .000 0.531 Large

effect

RDI_2011–

RDI_2012

0.010 2.921 29 .007 0.227 Large

effect

203

Period Mean t df Sig. (2-tailed)

RDI_2006 - RDI_2007 .068 8.609 29 0.000

Legend: RDI as a mean change score compared to maximum possible score (147)

Thus, the evidence presented here suggests that there is a significant increase in risk

disclosure over the period under examination, 2006-2012. This result supports

Hypothesis 1 (H1: There are significant differences in risk disclosure over the period

under examination, 2006-2012).

7.5 Discussion of results

Risk disclosure information is useful to investors who need such information to aid

them in making informed decisions (Linsley & Lawrence 2007; Solomon et al. 2000).

Following the comparisons made over the period 2006-2012, the general observation is

that there is an aggregate trend of an increasing score for corporate risk disclosure in the

banking industry in Bangladesh in an effectively voluntary institutional setting. The

increase in the upward trend is consistent with the increased importance of disclosure of

risks and uncertainties as well as the increased attention given to the topic by

international standard setters. The increase is also statistically significant between the

periods examined. Overall, the findings reported in this Chapter are consistent with the

predictions of theory, accounting regulatory developments and increased calls for

improved disclosure.

The content analysis in this Chapter provides an interesting insight into the nature and

quality of risk information disclosed (e.g. qualitative versus quantitative) by sample

banks in this study. This Chapter reveals that each category of risk disclosure is

increasing; however, Information and Communication risks dominate the upward trend

compared to the other six categories. Risk Types, Capital Disclosure, Strategic

Decisions and Government Regulation showed only slight change. Changes in the

26Table 7.12: Paired sample t-tests

204

Internal Corporate Governance and General Risk Information categories vary (both

upward and downward) throughout the period.

The sub-category risk categories under Risk Types suggests a significant upward trend

in Credit, Market and Liquidity risk disclosure categories from 2006 to 2010 whilst the

increasing rate decreases in the following years (2011-2012) for these categories. The

other two sub categories (Operational and Equities) also rise, though the increasing rate

varies over the period.

The qualitative and quantitative natures of risk disclosure show different trends in

changes between different years. Market and Equities risk disclosure suggest that

qualitative risk disclosure increases clearly across the period. Qualitative risk disclosure

also increases for Credit, Liquidity and Operational risk disclosure except for the year

2008. Only Equities risk shows a clear upward trend for quantitative disclosure.

Additionally, quantitative risk disclosures were lowest in year 2008 for all types (except

Equities). This is also validated when quantitative disclosure of Market risk was highest

in 2007.

The statistical tests reported in this Chapter demonstrate significant differences in risk

disclosure scores across the years. Moreover, on average, Non-Islamic banks disclose

more items compared to Islamic banks. This Chapter compares the total seven-year

period in three distinct periods (GFC, transition and post-GFC). Both parametric and

non-parametric statistical tests suggest the significance and large size effect of

disclosure changes across these three periods. The eta squared suggests the highest

effect (53.11 per cent) occurs during the transition time.


This Phase of the broader study provides a contribution to the financial reporting

literature as it offers an overview of the risk reporting practices of all listed banks in

Bangladesh across the seven-years, encompassing pre- and post the GFC. This Phase

employs a content analysis research methodology to investigate risk disclosure

205

practices. A disclosure category taxonomy was developed to classify the types of risk

disclosure by all banks. The findings from this exploratory research suggest an

increasing trend in banks’ risk reporting disclosure as predicted.

The analysis reveals significant changes in risk information disclosed by sample banks

over the period. The results also show a general increase in all types of risk disclosure

including Risk Types, Capital Disclosure, Internal Corporate Governance, Information

and Communication risks, Strategic Decision risks, General Risk Information and

Government Regulation categories. Tests of statistical analysis were carried out and

there are significant differences in risk disclosure scores across the period. In addition,

Non-Islamic banks disclose more risk items compared to Islamic banks.

The increase in risk disclosure could be because of increasing international regulation

through international standards that suggest disclosing information related to risks,

although there is no effective, enforced mandate in Bangladesh. Previous studies also

suggest that accounting regulations and market discipline are important factors driving

improvement in voluntary disclosure (Aebi, Sabato & Schmid 2012; Samad 2008).

Banks increase their voluntary disclosure to avoid additional requirements that are

detailed and perhaps costly requirements by regulators and accounting standards.

The results presented in this Chapter will be utilised in the following Chapters in order

to conduct further analysis in order to investigate the link between risk disclosure and

companies’ characteristics and sample banks’ performance. It is important to note that

the relation between the Risk Disclosure Index and the predictors is further analysed

through direct communications with regulators and banks’ representatives. The next

Chapter examines this qualitative interview data in order to enhance insights to the

findings from the quantitative risk disclosure data collected from annual reports.

206

CHAPTER 8: An Exploration of Banks’ Risk Disclosure Practices and

their Determinants in Bangladesh: Qualitative Analysis

of Interview Data

8.1 Introduction

Results from Phase One of this study (Chapter 7) found that although there was an

increasing risk disclosure trend over the period of analysis (from 2006 to 2012),

consistent with Hypothesis 140

, there was still minimal risk disclosure practices

exercised by banks in Bangladesh compared with an optimal level compiled from

international standards. Previous research also evidenced that although there is an

increasing trend in risk disclosure in annual reports, it remains at disappointing levels.

For example, Oliveira, Rodrigues and Craig (2011, p.818) argued that ‘prior studies

have found that risk disclosures are vague, generic, qualitative, backward looking, and

inadequate for the information needs of stakeholders’. Given that, it does seem

reasonable that corporate representatives’ opinions will be particularly important in

better understanding the current practices of corporate risk disclosure and their key

determinants.

The systematic presentation of qualitative data results in greater depth and richness of

data than would be attained from purely quantitative data within the context of

corporate risk disclosure by listed banks in Bangladesh. Therefore, this Chapter aims to

explore the perceptions of corporate representatives in relation to corporate risk

disclosure practices and their determinants. To achieve this objective, this study

provides qualitative data from in-depth interviews with senior executives of the

Bangladesh Securities and Exchange Commission, the Bangladesh Bank (Central Bank)

and risk management and reporting units from different listed banks within the sample

for this study.

40


207

The in-depth interviews (conducted during February-April, 2013) are used to enhance

and enlighten the findings from annual report data reported in the previous Chapter.

They are used also to inform the proposed models for testing the other Hypotheses and

to provide direct evidence to support or refute the proposition that larger banks

influence the risk reporting behaviour of smaller banks. Of crucial importance, however,

is the fact that the interview data is used also to support or refute the

assertion/assumption maintained throughout this thesis that Bangladesh presents an

ideal location in which to conduct this research. This is so due to the non-mandatory

and/or non-enforced nature of disclosures under the international standards used for

benchmark comparison (IFRS 7 and Basel II: Market Discipline).

The interview questions were semi-structured and were guided primarily by the research

objectives. The research method adopted within this Chapter is discussed in Chapter 6.

Interview results are presented in a structured manner according to the sequence of the

questions, reflecting the key themes associated with risk disclosure practices and their

determinants.

This Chapter is organised as follows. Analysis of interview data regarding risk

disclosure practices and the rationale for disclosing the extent of risk information

appears in section 8.2. Interviewees’ opinions about the determinants of risk disclosure

are discussed in section 8.3. Additional explanation from interviewees is presented in

section 8.4 and the Chapter concludes in section 8.5. Figure 8.1 provides an overview of

this Chapter.


Introduction (8.1)

Risk disclosure

practices (8.2)

Determinants of risk

disclosure (8.3)

Additional findings

(8.4) and Chapter

conclusion (8.5)

208

8.2 Risk disclosure practices and rationale for disclosure

The interviews began by seeking a general understanding of the bank’s risk disclosure

practices and rationale for disclosing the level of information currently being provided.

The initial review of interview transcripts reveals a significant degree of consistency

among the respondents. Consistent with the maintained assertion throughout this thesis

alluded to in the introduction, respondents indicated that their risk disclosure practices

are voluntary. In relation to their perceptions of change in risk disclosure over time,

some of the respondents stated that:

Professionalism in risk reporting is yet to develop in (the) Bangladesh market. Till now

risk disclosure is voluntary exercise and often not used as business tool. (Interviewee #

12)

…..certainly, there is an increased interest of risk reporting from stakeholders. If you go

back to the early 2000s, we did not receive any guidelines (about risk disclosure) from

Bangladesh Bank (Central Bank). But certainly, the last few years have seen an

increase in stakeholders’ interest, not just about what our risk management structure(s)

are, but what risk governance policies we use internally to manage our risk profile.

Therefore, there is a lot more interest from the regulatory bodies about how we are

managing our assets and liabilities and those sorts of things. (Interviewee #3)

I think we are seeing an increase in interest from the Central Bank for risk disclosure

about how we assess risk, how do we monitor risk and how do we manage our risk

appetite. I think what you have probably found in our annual reports is that the change

in reporting is based on the increasing reform of International Financial Reporting

Standards. (Interviewee #5)

The above quotes identify managers’ perceptions about the changing expectations of

stakeholders regarding provision of risk information. The quotes also reveal a perceived

change in stakeholders’ interest that has moved to demanding information about how

companies manage their risk profile via their governance policies. However, the current

risk disclosure in annual reports is still at a low level. Corporate bank representatives’

209

responses in relation to current risk disclosure by banking institutions are illustrated as

follows:

…..better assessment of risk required timely, accurate and reliable

information…..however, most of the bank(s) does (do) not use sophisticated risk

analysis or assessment software, tools or technique(s). Therefore, in absence of timely,

accurate and reliable information, corporate risk management practices is(are) partially

effective at assessing risk but not appropriate for proper risk management and reporting.

(Interviewee #13)

Another interviewee provided a similar view.

The credit risk computation of expected loss is not yet a practice in banks in

Bangladesh. The quantification of market, liquidity, operational and equities are

stipulated by Central Bank limitation (little guidance on quantification). (Interviewee

#7)

The above quotes identify managers’ perceptions about the lack of risk reporting

practices by banking institutions in Bangladesh. The quote immediately above also

supports the earlier discussion in this study (Chapter 3 Bangladesh: The Context of the

Study) in relation to institutional weaknesses. Under the prevailing regulatory

frameworks in Bangladesh, there is a lack of appropriate monitoring for implementation

of International Financial Reporting Standards (Sobhani, Amran & Zainuddin 2012).

Apart from this, non-compliance with the standards is often not reported and

disciplinary action is seldom instituted in Bangladesh (Chowdhury 2012).

At this stage of the interviews, the participants were advised about the ‘Risk Disclosure

Index’ (RDI), prepared in Phase One of the broader study, which includes different

types of risk disclosure comprising 147 specific risk-related items (refer Chapter 6,

Table 6.2). The researcher provided the interviewees with a copy of the Index

containing the list of information items. The objective was to find out whether the

respective bank representatives were aware of the item of risk disclosure with respect to

the international standards. Responses tended to show that despite the expectations of

the stakeholders, much of the information within the Index was missing from their own

annual reports. Typical responses included:

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I am sure that there are(is) some information missing. This is because there is a

conceptual gap between rules and practices. Bangladesh Bank did not provide us any

circular or directives on International Financial Reporting Standards. Currently,

Bangladesh Bank and Institute of Chartered Accountants of Bangladesh are working on

this and it does mean that we will consider this in the process. (Interviewee #5)

Information regarding market discipline (Basel II) and the responsibilities/duties of the

risk management division/unit need to be clear. (Interviewee #14)

The above quote identifies less disclosure with respect to Risk Disclosure Index items.

However, the Index is developed based on International Financial Reporting Standard 7

(IFRS 7) [Financial Instruments: Disclosures] and Basel II (Market discipline). Refer

to previous Chapters (Chapter 1, 2) IFRS 7 was issued in 2005 to become effective in

January 2007 and Basel II (Market discipline) in 2004, though; the interviewees were

conducted in 2013.

8.3 Determinants of risk disclosure

Based on the responses discussed in Section 8.2 about the current practices of corporate

risk disclosure, corporate representatives were asked to explain the motivations for such

disclosure. At this stage, the interviewee participants were advised about the underlying

factors, which were identified using agency and institutional isomorphism concepts (see

Chapter 5 Theoretical Perspective Underpinning the Research: Conceptual Framework

and Hypotheses) within this study. In addition to that, as the interview was conducted

with semi-structured questions, respondents were left to provide their opinion

voluntarily. The interviewees were asked whether, in their opinion, an independent

board, an independent audit committee, the number of risk committees, the debt to

equity ratio, total assets and the presence of a risk management unit are associated with

the risk disclosure practices of banking institutions in Bangladesh. The initial interview

transcripts indicated that interviewees’ opinions about the determinants of risk

disclosure were aligned with the model proposed in Chapter 5 to test Hypotheses 2-741

.

41

H2: The number of independent directors on the board is associated positively with the extent of risk

disclosure. H3: The number of independent directors on the audit committee is associated positively with

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A closer analysis of the themes contained within these transcripts revealed that the

underlying factors can be grouped into two categories: institutional isomorphism and

risk governance factors. Perceptions about each of these are summarised in the next

section.

8.3.1 Institutional isomorphism

With respect to the discussion in Chapter 5 (Theoretical Perspective Underpinning the

Research: Conceptual Framework and Hypotheses), the respondents were asked to

explain whether they face institutional pressure (such as; (1) demand from creditors; (2)

imitation from superior organisations; and (3) professionalism). In response to this

question, respondents argued that imitation of superior organisations and

professionalism were considered more powerful than creditors’ demands. The following

comments reveal some of the interviewees’ thoughts regarding this issue:

If investors want to know any information or any specific query, we have to provide

them because we need funds from them. However, they do not usually require

commercially sensitive information. I think they are more interested to know about

commercial returns rather than risk management kind of things. (Interviewee #10)

Certainly, investors’ are important to us. We need to validate that their investment is

safe. If they require any information, we are happy to provide that. Nevertheless, it is

important whether they have enough knowledge about risk related matters. For

example, they need to understand maturity profile of assets, non-performing loan(s),

and risk based ratio(s), or maturity mismatch. I think they only look for market goodwill

or television advertisement(s) rather than disclosure in annual reports. (Interviewee # 8)

This study has found that although investors are powerful, they are perceived by listed

banks’ managers to be more interested in profitability information than risk information.

the extent of risk disclosure. H4: The number of risk committees is positively associated with the extent

of risk disclosure. H5: Coercive isomorphic pressures are positively associated with the extent of risk

disclosure. H6: Mimetic isomorphism of larger banks influences smaller banks to provide more risk

disclosure. H7: Normative isomorphism is positively associated with the extent of risk disclosure.

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The corporate representatives further revealed their perception that lack of knowledge

limits investors’ understanding of risk assessment.

Another institutional isomorphism concept concerning risk disclosure is mimetic

isomorphism. Earlier discussion about mimetic isomorphism in Chapter 5 (Theoretical

Perspective Underpinning the Research: Conceptual Framework and Hypotheses) is

based on the Hypothesis that larger banks influence smaller banks to provide more

information. Responses include:

Definitely, we do follow better reporting format from others. Usually, big banks publish

better reports and communicate much information. We do follow their annual reports,

as they are successful and visible to stakeholders. (Interviewee #6)

Institute of Chartered Accountants of Bangladesh declares national awards for the best-

published annual report. It is our practice to look at best-awarded report as a

sample..........to my knowledge basically, large market share banks receive those awards.

It seems to me that larger banks disclose better. (Interviewee # 4)

The answers provided by the corporate representatives reveal smaller banks follow

larger banks’ reporting, consistent with the Hypothesis (H5: Mimetic isomorphism of

larger banks influences smaller banks to provide more risk disclosure.) posited in

Chapter 5. It is not possible to provide empirically derived evidence in relation to this

Hypothesis because it is not possible from secondary data to discern motivations for

actions by smaller banks in relation to their disclosures. Extant studies find that

disclosure of risk information assists companies in managing their reputation and public

visibility (Abraham & Cox 2007; Oliveira, Rodrigues & Craig 2011). This could

encourage smaller banks to disclose greater risk information. However, costs are

associated with disclosing information, which bigger banks can manage more easily.

One respondent though argued that cost of disclosure is not that material as it is a part of

a ‘business as usual’ approach:

There are costs associated with reporting, but it is not significant in relation to all other

costs. For example, it can reduce monitoring costs and information gap between the

shareholders and managers. (Interviewee # 1)

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Regarding normative isomorphism, respondents indicated that professionalism is a

crucial influence in explaining risk disclosure: banks seem to execute their specialised

knowledge and expertise through professionalisation. In the context of the theoretical

aspects (see Chapter 5 Theoretical Perspective Underpinning the Research: Conceptual

Framework and Hypotheses) of normative isomorphism, the respondents contended that

banks exercise professionalism by establishing a risk management unit. They further

argued that the risk management unit not only conducts stress testing for examining the

banks’ capacity in handling future shocks, but also deals with all potential risks that

might occur in future. The following comments reveal some of the interviewees’

thoughts regarding this issue:

We adopted policies that deal with managing different operational risk, internal control

and compliance-division in conjunction with the Risk Management Unit (RMU). RMU

has been performing the supervisory and monitoring works to manage operational risk.

(Interviewee # 10)

A similar view is provided by interviewees 8 and 11.

Certainly, (the) Risk Management Unit is putting its best effort roles and

responsibilities of individuals involved in risk taking as well as managing it. We formed

a separate Risk Management Unit to formulate of overall risk assessment and

management policies, methodologies, guidelines, and procedures for risk identification,

risk measurement, and risk monitoring. (Interviewee # 8)

(The) Risk Management Unit in our bank is arranging monthly meeting on various

issues to determine strategies in consistency with risk management policy, which can

measure, monitor and maintain acceptable risk level of the bank and plays an advisory

role for risk reporting. (Interviewee #11)

The above statements emphasise that risk management units address different areas of

risk and risk mitigation management tools and techniques guided by experienced and

knowledgeable members. The respondents claimed that risk management units prepare

quarterly minutes addressing different areas of risk and also develop a procedure for

measuring inclusive capital adequacy in relation to bank risk summary and policy to

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maintain the bank capital at an adequate level following the Risk Based Capital

Adequacy guideline from Bangladesh Bank (Bangladesh Bank 2013b).

8.3.2 Risk governance factors

Discussion in Chapter 5 argued that an effective monitoring system could reduce

information asymmetry between shareholders and managers that depends on an

independent board, independent audit committee and number of risk committees.

Corporate respondents were asked whether, in their opinion, these factors are associated

with risk disclosure. Based on responses by the corporate representatives, the risk

committee is an important determinant in explaining corporate risk disclosure.

Additionally, most of the interviewees mentioned that board independence is a partially

effective determinant. However, none of the respondents pointed to audit committee

independence as a crucial factor for risk disclosure. The following comments reveal

some of the interviewees’ thoughts regarding this issue:

Our initiatives for corporate risk disclosure come from internal risk governance factor,

such as risk committee. The members in risk committee come from very distinguished

educational backgrounds and they are responsible for managing all risks types across

the bank. By identifying, monitoring and managing the banks’ current and potential

operational risks exposure, risk committees inform internal audit and executive board of

issues affecting operational risks. (Interviewee #09)

We established risk committees to support effective risk governance throughout the

organisation. They are responsible for determining general principles for measuring,

managing and reporting the bank’s risks. They also develop risks policies for business

units and determine the overall investment strategy. (Interviewee # 06)

The above quotes emphasise the importance of risk committees in risk identification and

risk communication. The quotes also reveal that by establishing risk committees, banks

are more likely to create a risk management framework and follow up on reports

prepared by internal audit and inform the executive board of issues. A previous study

found the effectiveness of risk committees in overseeing all relevant risks within the

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organisation (Aebi, Sabato & Schmid 2012). However, the effectiveness of risk

committees depends on whether members of risk committees are knowledgeable

members.

Regarding board independence, most respondents indicated that an independent board is

a crucial determinant for risk disclosure. They emphasised independent boards, and

members’ educational background and personal attributes in making corporate risk

disclosure decisions. For example, independent directors on the board are more highly

educated and are more aware of risk related issues, and the market demand for such

disclosure. Responses include:

I think independent member(s) in(on) the board is considered as one of the important

for governance mechanisms. We believe (a) higher proportion in the independent

directors in the board develop(s) our relationship with stakeholders. (Interviewee # 02)

Our driving force for corporate risk disclosure is that we have adequate independent

members in(on) the board. They provide our management with their better advice due to

their experience, expertise and network. (Interviewee #01)

The answers provided by corporate representatives reveal that a higher proportion of

board independence leads to higher monitoring. Using their experience, independent

directors monitor the opportunistic behaviour of management independently and

provide a larger number of risk disclosures. Previous studies found inconclusive results

in relation to board independence and voluntary disclosure. For example, some studies

found that higher percentage of independent directors leads to higher quality

management decisions (Chen & Jaggi 2000; Pearce & Zahra 1992). Other studies found

that a large percentage of independent directors lead to excessive monitoring (Baysinger

& Butler 1985; Eng & Mak 2003). Typical responses included:

Well…. to me it is not possible to make (the) board independent. Most of the members

in(on the) board are either politically influenced and/or corrupted. For example, when

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the central bank sent an observer to a weak bank (according to CAMELS42

rating) and if

the observer asks for any suggestion that needs to be acted upon, board has a tendency

to avoid the situation using political power. (Interviewee #12)

8.4 Additional findings from interviewee

This section presents the additional and alternative explanations that might emerge from

the interview data. Section 8.2 revealed the existence of an expectation gap in relation to

corporate risk disclosure. With this issue in mind, corporate representatives were asked

to explain ‘why banks are not providing more information’. In response to these

questions, the rest of this Chapter provides a discussion in relation to corporate risk

disclosure practices by banking institutions in Bangladesh.

8.4.1 Institutional weakness

The corporate representatives in this study revealed that legal and institutional weakness

exists in corporate risk reporting by banking institutions in Bangladesh. Previous study

also identified this impediment towards adoption of a Western-style corporate

governance model. For example, Siddiqui (2010) identifies institutional weaknesses in

Bangladesh as, ‘highly concentrated ownership structure, lack of shareholder activism,

presence of a weak capital market, absence of second-order institutions and poor legal

structure’ (p. 209). One respondent shared his experience as:

Certainly corporate governance issues exist in overall system. Recently we faced

‘Hallmark loan Scandal43

’. I think this is not only the one. If proper and through

investigations and comprehensive audit are conducted many more Hallmarks may come

into light, which may put the entire banking sector in an embarrassing situation and the

confidence of the depositors may go shattered. (Interviewee #11)

42

CAMELS is an international bank rating system based on capital adequacy (C), Asset quality (A),

Management quality (M), Earnings (E), Solvency (L), Sensitivity to market (S). Central bank assigns

scores to each bank to identify whether banks need attention (refer. Chapter 3) 43

In the country’s biggest banking scam, the Hallmark Group embezzled around Tk 1,492 crore.

According to the Anti-Corruption Commission findings, the ‘Hallmark Group’ in liaison with bank

officials opened 2.3 Letter of Credits (LC) a minute, whilst usually this needs a minimum of 1.3 to 2

hours for creating one new LC. The Commission said that it was a lone example in the country’s history

that so many LCs were opened in a day (Progress Bangladesh 2014).

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Several studies have identified that boards of directors in Bangladesh are dominated by

family members (Hopper et al. 2003; Siddiqui 2010; Uddin & Choudhury 2008b). They

keep the majority of the shareholding within their family connections, which means that

a small number of shareholders control the majority of shares and attain major

decision-making status (Bangladesh Enterprise Institute 2003). For example, Hopper et

al. (2003) observed that if a father who became chairperson then other family members

became chief executive officer, executive director and marketing director. Thus, the

whole family became members of the board of directors. However, minority

stakeholders need to be included in making economic decisions in relation to allocation

of economic resources (Darmadi & Sodikin 2013). A corporate representative in this

study noted:

….in reality, this family (showing directors’ pictures from annual report) is managing

our business affairs. I should say they play the advisory role even they don’t have

specialised knowledge. In fact, independent directors often follow sponsor directors’

advice. (Interviewee #13)

The quote above reveals that in practice, banks are virtually controlled and managed by

a few sponsors. Uddin and Choudhury (2008b) observed that owners of banks in

Bangladesh completely control management activities. Additionally, family members

(hence directors) could instruct their financial reporting devision to make favourable

annual reports and are hardly monitored by the Bangladesh Securities and Exchange

Commission or by the Registrar of Joint Stock Companies (Khan 2004; Uddin &

Hopper 2003; Ali, Ahmed and Henry 2004).

According to the Companies Act 1994 (Section 213), auditors are required to provide

their view on the truth and fairness of the state of accounts. However, the responses

from corporate representatives in this study reveal that their (audit) report is

questionable. Typical responses include:

Well, who wants to lose client when audit fees are very poor? They (auditor) sign

whatever we produce. The true and fair view statements are nice words in annual report

only rather in real practice. (Interviewee #3)

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Another interviewee provided a similar view.

Theoretically, external auditors are independent. But unfortunately, external auditors do

not have power. They just sign the internal auditors’ report. (Interviewee #11)

The quote above reveals perceived auditors’ non-compliance with the true and fair

declaration. Previous study also found incompetence in external audit firms (Hopper et

al. 2003; Uddin & Choudhury 2008b) and lack of adequate disclosure (Ahmed &

Courtis 1999; Ahmed & Islam 2004). Furthermore, Uddin and Choudhury (2008b,

p.101) provided evidence that ‘banks are very lucrative clients and in most cases the

audit firms are also linked with the personal businesses of the bank owners. As a result,

the auditors tend to give in to the demands of the bank owners and prepare audit reports

in the way the banks want them to’. Besides, Uddin and Choudhury (2008b) further

revealed that majority of the banks’ internal audit reports demonstrated fraud

information. One respondent commented as:

For true and value representation of information and to maintain auditors’

independence, we need transparent internal control system…also external auditor need

to be appointed externally (such as Government) as third party…and finally we need to

think about audit fee. (Interviewee #9)

8.4.2 Political interference

Discussion in Chapter 2 (Risk Reporting is an Issue of Concern) revealed that the

political economy in Bangladesh is distinguishable by a number of economic,

traditional, and political relationships that make it distinct from general Anglo-

American context. The political environment in Bangladesh is based on patron-client

relationships (Sobhan & Ahmad 1980). This suggests that colonial heritage, the

economic policies of the British colonial government and the economic position of

different ethnic groups before and after independence, have all influenced the growth

and development of political and business relationships in Bangladesh. Bliss and Gul

(2012) also revealed that politically patronage firms are positively associated with debt

financing.

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It emerged from the responses that political interference implements undue influence on

board governance. This was raised as:

It is impossible for us to take into account the information needs of too many

stakeholders. If we do so, we would not be able to fulfil our main obligations. We

disclose relevant level of information and decide what should be included in order to

meet reporting requirements. (Interviewee #1)

The Central Bank sends observers to weak banks. However, what can Central Bank

does when the board itself has a motive to implement their decision using political

influence? …law exists literally but in reality, it is difficult to exercise Central Bank’s

power to those banks. (Interviewee #13)

We don’t mind providing disclosure but this depends on how the board perceives what

the implication will be. Audit committee would like to be transparent but when it comes

to the board decisions, they may choose not to disclose them because of political

implications of some of the information. I think political interference and government

pressure assist the board to exercise this sort of unethical power. (Interviewee #10)

Evidence from this last interviewee reveals that politics does influence disclosure

decisions, especially in companies that have politicians on their board. These types of

banks felt somewhat protected against external threats (such as pressure groups) which

could impair their economic interest because of their connections with government. The

politicians on boards of directors (as representatives of the government) influence the

board as to what and how much to disclose.

Additionally, a severe agency problem may occur when there is political influence by

government and/or when politicians are board members. The accounting system of a

bank could be affected when there is such political influence. Politicians influence

managers to report selective information or to present annual reports in their best

interests (Watts & Zimmerman 1978). Extant studies also find that political influence is

negatively associated with financial reporting quality (Agrawal & Knoeber 2001;

Belkaoui 2004).

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8.4.3 Lack of central bank autonomy

High attention was given to Central Bank autonomy by all the interviewees. As a

government organisation, the Central Bank performs the entire core monetary and

financial stability function as well as regulating and supervising financial institutions in

the country. Central Bank autonomy refers to the extent to which the Central Bank

executes the functions independently and has legislative control (Boylan 2001). The

degree of autonomy delegated to the Central Bank affects the structure of accountability

to ensure the intended delegated authority (Mehrling 2005).

The Central Bank in any country governs monetary policy, acts as a financial agent for

government and exercises supervisory and regulatory duties to establish banking sector

stability. Therefore, the Central Bank should have political and financial autonomy

(Lybek 2004). The International Monetary Fund (IMF) also supports Central Bank

autonomy and accountability for sustainable economic growth and good governance

(IMF 2012).

In the context of Bangladesh, all the interviewees perceived that the Central Bank

cannot exercise its full autonomy. Responses include:

We cannot control the corruption made by board. Additionally, the Ministry of Finance

has excessive power on banks. If Central Bank enjoys autonomy without the

intervention of the Ministry of Finance….board could not manipulate the decision of

the Central Bank. Now it is a question if the Central Bank can operate independently.

(Interviewee #14)

The above quote highlights the importance of exercising Central Bank autonomy over

banking institutions. The response above reveals also the institutional weakness of the

Central Bank in Bangladesh. This is supported by another cross country study

conducted by Ahsan, Skully and Wickramanayake (2009). Using the sample of

Bangladesh and Australia this study examined Central Bank independence and

governance. By using an index to assess the association between governance and

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Central Bank independence in 1991-2008, they found that these two are significantly

weaker in Bangladesh than Australia.

8.4.4 Lack of accountability

Another potential reason for banks not disclosing risk information is that the primary

aim of banks is to maximise profit for the benefit of their shareholders, rather than

accept a broader accountability to other stakeholders. The interview responses suggest

that disclosing commercially sensitive information has a potential impact on the

profitability of banks. Thus, interviewees indicated a shareholder-oriented view by

focusing on the commercial return of banks. The following comment reveals the

interviewees’ thoughts regarding the issues:

We used to balance commercial sensitivity. We only report what is in the best interests

of the stakeholders and we have commercial information that needs to be protected.

When we disclose information, we make sure that shareholders’ interests are not

compromised. We cannot disclose the information that has a negative impact on our

commercial return. (Interviewee #3)

The statement emphasises that managers’ decisions to disclose or not to disclose

information are based on an ‘economic’ rationale rather than on the basis of a duty of

accountability towards a wider stakeholder audience. Avoiding the disclosure of

commercially sensitive information might protect the interests of shareholders,

however, it is very difficult to envisage stakeholder accountability being established in a

situation where managers have such a concern for maximising shareholder value

(Cooper & Owen 2007). From the views expressed here, it can be concluded that

economic motivation plays a dominant role relative to the broader issues associated with

accountability.

8.4.5 Lack of demand from governments

Most of the interviewees argued that banks do not disclose due to lack of demand from

government. If it is a particular government requirement, then banks feel a need for

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compliance. The responses suggest that, consistent with the maintained assertion in this

thesis, at present banks do not perceive a great deal of pressure from the government

due to a lack of current regulatory requirements pertaining to corporate risk disclosure.

Additionally, several interviewees are concerned about the effectiveness of existing

laws in relation to the internal control system. Responses include:

If government wants any information, we provide it. However, I don’t see government

pressures us for such information. There is no legal obligation for us to report on

disclosure. (Interviewee #2)

The interview responses indicated that stakeholders perceived as powerful do not

demand more information; therefore, they are not exercising influence on companies to

motivate them to disclose corporate risk information. Due to the lack of demand from

powerful stakeholders, it is unlikely that banks would be motivated to disclose more

rather than less information.

8.4.6 Lack of education

Corporate risk disclosure and the benefits of disclosure are new concepts to the

corporate bank representatives in Bangladesh. Besides, stakeholders also have lack of

knowledge about risk disclosure. Interviewees suggested that there is a need for

education and awareness of corporate representatives, regulators and stakeholders in

relation to corporate risk disclosure. They emphasised that corporate risk disclosure

benefits the internal control system and enhances external stakeholders in understanding

of the risk profile, risk appetite and future investment possibility. The following

comments reveal the interviewees’ thoughts regarding the issues:

…..important is whether shareholders and other stakeholders are educated. For example,

they need to understand the quality of asset, non-performing loan structure, risk based

ratio and maturity profile of assets. (Interviewee #4)

I think enterprise owners need to be educated to implement standards and good

accounting practices. (Interviewee #6)

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The responses above indicate the need for education and awareness to enhance

corporate risk disclosure as Bangladeshi banks are still at an infancy stage in this

respect.

8.4.7 Brief and concise reports

The respondents also emphasised that they need to keep the annual reports as brief and

concise as possible, the implication being that they elect not to disclose all the

information in annual reports. As stated by one respondent:

We do not seek to make our annual reports very long and difficult to read, however, we

aim to provide fully comprehensive documents for investors to find the relevant

information. (Interviewee #9)

Another respondent (Interviewee No. 7) emphasised that there are ways to communicate

with stakeholders other than in annual reports. They put importance and potentiality of

reporting via other media such as online or websites as an alternative means of

communication. These can benefit in several ways. For example, they can facilitate

speedy, two way interaction between potentially many participants, providing much

readily accessible information so that people can become more informed. Therefore, it

is possible to make concise and brief reports and make the website disclosure more

comprehensive, which might lead banks to elect not to disclose all the information in

their annual reports.


The discussion within this Chapter explores corporate and regulators representatives’

observations about risks disclosure practices and their determinants. The Chapter also

explores the potential reasons for the lack of disclosure pertaining to corporate risk from

a company perspective. Having provided an insight into risk disclosure practices,

interviews were utilised to understand the factors responsible for current low level

disclosure practices. The interview responses in this study suggest that institutional

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isomorphism (mimetic and normative), risk committees and board independence are key

contributing factors to corporate risk disclosure.

Additionally, perceptions of political interference, Central Bank autonomy, limited

perception of accountability, demand from powerful stakeholders, lack of education of

users of financial information, keeping annual reports brief and concise, appear to

contribute to the apparent lack of corporate risk disclosure.

The corporate and regulator representatives argued that the reporting format used by

larger banks encourages smaller banks to provide better reporting. That is, the risk

profile of larger banks assists in managing accountability, transparency, reputation and

public visibility. This evidence supports the mimetic isomorphism Hypothesis posited in

Chapter 5. The respondents argued also that experienced and knowledgeable members

in the risk management unit assists banks to identify and monitor risks well. Besides,

interview responses suggest that risk committees in banks work for risk identification,

inform internal audit and executive members of the board about banks’ current and

potential risks exposures. The respondents also emphasised the importance of an

independent board in making sound decisions in relation to corporate risk disclosure.

The interview data reveal that corporate risk disclosure practices are still at a low level.

The reasons for non-disclosure can be identified from interview data. The interviews in

this study revealed that because of institutional weaknesses, lack of disciplinary action,

and political interference, banks are not motivated to disclose a great deal of corporate

risk information. That is, undue political power is exercised on the governance structure

when politicians are board members.

The interviewee data also emphasised the importance of Central Bank autonomy. The

interviewee data reveals that the Central Bank in Bangladesh cannot use full autonomy

to execute its functions independently. There was a particular concern about powerful

stakeholders requiring disclosure. This study found that banks are not motivated to

disclose a great deal of information if particular concern is not raised by powerful

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stakeholders. Hence the thrust of the qualitative evidence is to support the maintained

assumption or assertion made very early in thesis, that Bangladesh creates an ideal

institutional setting in which to investigate risk disclosure and its determinants because

of both the lack of mandate and lack of enforcement over what mandate does exist.

Examining risk disclosure in a setting with highly regulated disclosure of risk issues

would not provide insights as to disclosure determinants because there would be little

variation between actual disclosures and those required by international standards.

Apart from the low mean actual percentage compliance with the international standards

at 62 per cent, as reported in the previous Chapter (Table 7.1), demonstrating wide non-

compliance with the international standards of relevance to this thesis, the qualitative

evidence presented in this Chapter from regulators and bank representatives is difficult

to dispute.

Interview data further reveal that emerging legislative requirements associated with risk

disclosure would influence banks’ disclosure to avoid regulation such as market

penalties. This assists accounting regulators and legislators in developing reporting

requirements by understanding motives for encouraging banks to provide risk disclosure

information. The idea behind mandatory disclosure is that ‘if all companies are

disclosing there can be no competitive advantages by non-disclosure’ (Solomon &

Lewis 2002, p.166). Therefore, this study suggests that introducing new legislation and

standards for disclosure of corporate risk disclosure may be able to narrow the apparent

lack of disclosure in Bangladesh.

The qualitative findings from this Chapter are referred to further in the following

Chapters when conducting further analysis of quantitative data gathered from annual

reports in order to examine the link between risk disclosure and bank characteristics.

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CHAPTER 9: Factors Underlying Risk Disclosure-Descriptive,

Univariate and Bivariate Analyses

9.1 Introduction

Chapter 7 reported the results of the risk disclosure content analysis and for

convenience and completeness within this Chapter, some of the statistics reported in

Chapter 7 are repeated here. Those results showed that there exists variation in the

extent of risk disclosure practices in Bangladeshi banking institutions. Phase Two of

this broader study seeks to identify the factors behind such variation. Chapter 5

explained the theoretical background for several hypothesised factors thought to explain

risk disclosure variation. Based on the discussion in Chapter 5, the present Chapter

seeks to examine on a univariate basis the relationship between the Risk Disclosure

Index and bank specific characteristics, such as board independence, audit committee

independence, the number of risk committees, debt to equity ratio, total assets, and the

presence of a risk management unit. Appropriate statistical tests are performed to assist

in understanding these relationships.

This Chapter reports results from descriptive and inferential analysis. Descriptive

statistics summarise data quantitatively without employing a probabilistic formulation

about the phenomena under consideration of each relevant variable (Field 2009).

However, inferential statistics such as Pearson correlations, t-statistics and chi square

statistics enable inferences from secondary data in order to make inferences that are

more general. The Chapter begins with descriptive statistics, univariate analysis using t-

tests and analysis of variance (ANOVA) results that describe the hypothesis and control

variables included in this study.

This Chapter is organised as follows: section 9.2 presents information about the sample

companies, section 9.3 presents the descriptive statistics for the predictor variables

(board independence, audit committee independence, number of risk committees, debt

to equity ratio, total assets, and the presence of a risk management unit) and control

variables (board size, auditor type and age of company). Section 9.4 compares the

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significance of mean values across the period using ANOVA, section 9.5 reports the

bivariate correlation analysis and section 9.6 summarises the Chapter’s findings and

provides a conclusion. Figure 9.1 provides an overview of this Chapter.

9.2 Sample and source of data

The procedures used to make the sample choice and selection of the sample are

explained in the research method Chapter (Chapter 6). The sample is based on 210

bank-year observations consisting of the population of 30 banks listed on the Dhaka

Stock Exchange of Bangladesh over each of seven-years from 2006 to 2012.

9.3 Descriptive statistics

This section reports descriptive statistics for key variables. Table 9.1 presents the

descriptive statistics for dependent, independent and control variables. The table

presented descriptive statistics for Full sample (210 bank-year observation) and sub

sample (Non-Islamic and Islamic). There are two categorical variables in the model

described in Chapter 6: the presence of a risk management unit (independent variable)

and the presence of a multinational linked auditor (control variable). The Risk

management Unit (RMU) variable is dichotomous and coded as 1 if bank has a risk

management unit and 0 if not.

The presence of a multinational linked auditor (ML) is coded as 1 if a big four

international audit firm is present and 0 if not. As discussed in Chapter 6, the five

continuous variables employed in this study are board independence (BI), audit


Introduction (9.1) Sample and source

of data (9.2) Descriptive

statistics (9.3)

Univariate

analysis (9.4)

Bivariate analysis

(9.5)

Chapter conclusion

(9.6)

228

committee independence (ACI), number of risk committees (RC), debt to equity ratio

(DE) and total assets (TA). BI is measured as the proportion of independent members

compared to total board members. ACI is measured as the proportion of independent

members compared to total audit committee members. RC is measured as the total

number of risk committees, DE is total debt divided by total equity. There are also two

continuous control variables: board size and age. Tables 9.1 and 9.2 present descriptive

data for the pooled sample of 210 firm-years and for 30 banks for each year

respectively.

As shown in Table 9.1 and as reported in greater detail in Chapter 7, all sample banks

provide some extent of risk disclosure in their annual reports. Table 9.2 reports

descriptive statistics for each year. Table 9.1 reports that the average Risk Disclosure

Index score is 62 per cent (for the pooled data) across the period (2006-2012) with a

minimum of 18 and maximum 87 per cent. Table 9.2 (panels A to G) presents results

showing that the Risk Disclosure Index for sample banks ranges from a mean of 43 per

cent to 77 per cent over 2006-2012.

229

Legend: Where, RDI denotes Risk Disclosure Index, BI denotes board independence measured as proportion of independent directors on the board. ACI

denotes Audit Committee Independence measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE

denotes the debt equity ratio. TA denotes total assets, BS denotes the number of board members, AG denotes age measured as numbers of years from

incorporation, RMU denotes presence of a risk management unit, ML denotes the presence of a multinational linked auditor.

44 TA is in billion BDT. Exchange rate taka (BDT) per U.S.A dollar - 81.863 (2014 est.);74.152 (2013 est.) .

27Table 9.1: Descriptive statistics by complete sample (bank years N= 210) and sub-sample (Islamic N=49, Non-Islamic N=161)

Full sample (N=210) Non-Islamic banks (N=161[77%]) Islamic banks (N=49[23%])

Dependent and continuous independent variables

Mean Median Std. Dev. Mean Median Min. Max. Std. Dev. Mean Median Min. Max. Std. Dev.

RDI 0.62 0.64 0.19 0.65 0.67 0.20 0.87 0.17 0.52 0.53 0.18 0.83 0.19

BI 0.05 0.05 0.04 0.05 0.06 0.00 0.25 0.04 0.03 0.00 0.00 0.20 0.04

ACI 0.15 0.20 0.14 0.16 0.20 0.00 0.33 0.14 0.10 0.00 0.00 0.33 0.13

RC 1.83 1.00 1.37 1.98 2.00 0.00 6.00 1.45 1.37 1.00 0.00 3.00 0.91

DE 0.10 0.10 0.14 0.11 0.10 0.13 0.71 0.09 0.06 0.10 1.43 0.21 0.22

TA44 84.18 68.00 82.27 82.88 71.00 15.00 824.00 70.90 88.45 47.00 15.00 502.00 112.64

BS 13.86 14.00 4.40 13.54 14.00 6.00 23.00 4.14 14.90 14.00 5.00 23.00 5.07

AG 17.72 14.00 9.70 18.32 14.00 7.00 53.00 10.28 15.75 13.00 5.00 31.00 7.24

Categorical

independent

variables

Proportion (%) of banks

coded 1

Proportion (%) of banks coded 1 Proportion (%) of banks coded 1

RMU (presence) 59.5 62.1 51.0

ML (Big 4auditor) 78.6 82.2 67.3

230

Table 9.2 presents average board independence, audit committee independence and

board size, which increases each year from 2006 to 2012 (BI 2 to 7 per cent, ACI 9 to

20 per cent; and BS 12.20 to 14.77), while the pooled data shows in Table 9.1 that the

average BI is 5 per cent and ACI is 15 per cent. The average number of risk committees

and the presence of a risk management unit increase respectively from 2006 to 2012.

Consistent with good governance principles, the increasing attention to risk

management indicates a positive approach by banks to the two international standards of

most relevance to this study (IFRS 7 Financial Instruments: Disclosures and Basel II

Market Discipline).

The average debt to equity ratio (DE) is 10 per cent and ranges from 7 per cent to 11 per

cent (see Table 9.2) across the years. The trend in DE decreases from 2006 to 2009-

2010 and rises in 2011 and 2012. DE falls in 2009-2010, indicating that debt-holders

have lower debt in that period. This is consistent with banks expending less in capital

expenditure as a safety measure after the GFC (2007-2008). The average total assets for

the pooled data is 84.18 billion BDT (see Table 9.1). Table 9.2 (Panel A-G) shows that

total assets is increasing over the period from 2006 to 2012, ranging from 43.67 to

118.27 billion BDT. The proportion of banks with risk management units (RMU) and a

big four auditor are 59 and 77 per cent respectively. These proportions suggest that over

half of the banks run risk management units while one-fifth of banks are not affiliated

with the presence of a big four-audit firm.

The means for the other two control variables, age and board size, also change over

time. Further, it is important to mention that to measure total assets, board size and age

for inclusion in the regressions, the natural logarithm of the numbers is calculated.

231

Full sample (N=30) Non-Islamic banks (N=23) Islamic banks (N=7)


Mean Median Std.

Dev.

Mean Median Min. Max. Std.

Dev.


Dev.

RDI 0.43 0.47 0.15 0.46 0.52 0.20 0.70 0.15 0.35 0.29 0.18 0.56 0.14

BI 0.02 0 0.03 0.02 0.00 0.00 0.09 0.03 0.02 0.00 0.00 0.06 0.03

ACI 0.09 0 0.12 0.08 0.00 0.00 0.33 0.12 0.13 0.11 0.00 0.33 0.14

RC 0.93 1 0.83 1.09 1.00 0.00 3.00 1.00 0.71 1.00 0.00 1.00 0.49

DE 0.11 0.11 0.07 0.11 0.11 0.06 0.38 0.08 0.10 0.10 0.03 0.19 0.07

TA45

43.67 35.5 38.41 41.00 42.00 21.00 76.00 15.43 52.43 24.00 16.00 230.00 78.37

BS 12.2 12.5 3.8 11.74 12.00 6.00 20.00 3.39 13.71 14.00 5.00 22.00 4.92

AG 13.77 7 6.63 15.00 11.00 7.00 47.00 10.14 13.00 11.00 5.00 25.00 7.59

Categorical independent variables

Proportion of banks

coded 1

Proportion of banks coded 1 Proportion of banks coded 1

RMU (presence) 20 17.4 28.6

ML (Big

4auditor)

77 82.6 57.1

Legend: Where, RDI denotes Risk Disclosure Index, BI denotes board independence measured as proportion of independent directors on the board. ACI denotes Audit Committee Independence

measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the debt equity ratio. TA denotes total assets, BS denotes the number of

board members, AG denotes age measured as numbers of years from incorporation, RMU denotes presence of a risk management unit, ML denotes the presence of a multinational linked auditor.

45 TA is in billion BDT. Exchange rate taka (BDT) per U.S dollar - 81.863 (2014 est .);74.152 (2013 est .)

28 Table 9.2 (Panel A): Descriptive statistics year 2006 (N=30)

232



Mean Median Std.

Dev.


Dev.


Dev.

RDI 0.5 0.52 0.17 0.55 0.56 0.28 0.80 0.15 0.39 0.40 0.19 0.61 0.15

BI 0.03 0 0.05 0.04 0.00 0.00 0.17 0.05 0.02 0.00 0.00 0.07 0.03

ACI 0.1 0 0.13 0.09 0.00 0.00 0.33 0.13 0.14 0.20 0.00 0.33 0.14

RC 0.93 1 0.94 1.05 1.00 0.00 3.00 1.05 0.71 1.00 0.00 1.00 0.49

DE 0.12 0.12 0.07 0.12 0.12 0.07 0.40 0.08 0.11 0.11 0.02 0.21 0.07

TA46 50.47 43 41.25 48.23 47.00 22.00 81.00 16.14 57.29 26.00 17.00 250.00 85.08

BS 12.47 13.5 3.75 11.95 12.00 6.00 20.00 3.37 13.71 14.00 5.00 22.00 4.92

AG 15.77 12 9.63 15.95 12.00 8.00 48.00 10.29 13.71 12.00 6.00 26.00 7.43


Proportion of banks coded

1



ML (Big

4auditor)

77 86.4 57.1

Legend: Where, RDI denotes Risk Disclosure Index, BI denotes board independence measured as proportion of independent directors on the board. ACI denotes Audit

Committee Independence measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the debt equity ratio.

TA denotes total assets, BS denotes the number of board members, AG denotes age measured as numbers of years from incorporation, RMU denotes presence of a risk

management unit, ML denotes the presence of a multinational linked auditor.

46 TA is in billion BDT. Exchange rate taka (BDT) per U.S.A dollar - 81.863 (2014 est .);74.152 (2013 est .)

29Table 9.2(Panel B): Descriptive statistics year 2007 (N=30)

233


Dependent and continuous independent variables Mean Median Std. Dev. Mean Median Min. Max. Std. Dev. Mean Median Min. Max. Std. Dev.

RDI 0.53 0.57 0.16 0.56 0.58 0.23 0.80 0.14 0.40 0.41 0.19 0.61 0.15

BI 0.05 0.06 0.04 0.05 0.07 0.00 0.10 0.04 0.02 0.00 0.00 0.07 0.03

ACI 0.09 0 0.15 0.11 0.00 0.00 0.33 0.16 0.04 0.00 0.00 0.25 0.09

RC 1.23 1 1.07 1.17 1.00 0.00 3.00 1.15 1.43 1.00 1.00 3.00 0.79

DE 0.11 0.11 0.08 0.12 0.11 0.09 0.45 0.09 0.09 0.10 0.04 0.13 0.06

TA47 85.77 56 144.56 93.61 58.00 31.00 824.00 160.38 60.00 31.00 19.00 230.00 75.34

BS 13.27 14 3.45 13.13 14.00 6.00 20.00 2.87 13.71 14.00 5.00 23.00 5.22

AG 16.77 13 9.63 17.39 13.00 9.00 49.00 10.27 14.71 13.00 7.00 27.00 7.43


Proportion of banks coded 1 Proportion of banks coded 1 Proportion of banks coded 1


ML (Big 4auditor) 80 87 57.1

Legend: Where, RDI denotes Risk Disclosure Index, BI denotes board independence measured as proportion of independent directors on the board. ACI denotes Audit

Committee Independence measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the debt equity

ratio. TA denotes total assets, BS denotes the number of board members, AG denotes age measured as numbers of years from incorporation, RMU denotes presence of a risk

management unit, ML denotes the presence of a multinational linked auditor.

47 TA is in billion BDT. Exchange rate taka (BDT) per U.S.A dollar - 81.863 (2014 est .);74.152 (2013 est .) .

30Table 9.2(Panel C): Descriptive statistics year 2008 (N=30)

234




RDI 0.62 0.64 0.19 0.65 0.67 0.20 0.87 0.17 0.52 0.53 0.18 0.83 0.19

BI 0.05 0.05 0.04 0.05 0.06 0.00 0.25 0.04 0.03 0.00 0.00 0.20 0.04

ACI 0.15 0.20 0.14 0.16 0.20 0.00 0.33 0.14 0.10 0.00 0.00 0.33 0.13

RC 1.83 1.00 1.37 1.98 2.00 0.00 6.00 1.45 1.37 1.00 0.00 3.00 0.91

DE 0.10 0.10 0.14 0.11 0.10 0.13 0.71 0.09 0.06 0.10 1.43 0.21 0.22

TA48 84.18 68.00 82.27 82.88 71.00 15.00 824.00 70.90 88.45 47.00 15.00 502.00 112.64

BS 13.86 14.00 4.40 13.54 14.00 6.00 23.00 4.14 14.90 14.00 5.00 23.00 5.07

AG 17.72 14.00 9.70 18.32 14.00 7.00 53.00 10.28 15.75 13.00 5.00 31.00 7.24


Proportion of banks coded 1 Proportion of banks coded 1 Proportion of banks coded 1

RMU (presence) 59.5 62.1 51

ML (Big 4auditor) 78.6 82.2 67.3


measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the debt equity ratio. TA denotes total assets, BS denotes the number of

board members, AG denotes age measured as numbers of years from incorporation, RMU denotes presence of a risk management unit, ML denotes the presence of a multinational linked auditor.


31Table 9.2(Panel D): Descriptive statistics year 2009 (N=30)

235




RDI 0.71 0.75 0.14 0.74 0.77 0.38 0.87 0.13 0.62 0.66 0.37 0.79 0.14

BI 0.05 0.05 0.04 0.06 0.07 0.00 0.13 0.04 0.03 0.05 0.00 0.07 0.03

ACI 0.19 0.23 0.15 0.22 0.33 0.00 0.33 0.14 0.08 0.00 0.00 0.33 0.14

RC 2.37 2 1.3 2.61 2.00 1.00 6.00 1.31 1.57 1.00 1.00 3.00 0.98

DE 0.09 0.09 0.04 0.09 0.09 0.01 0.20 0.04 0.08 0.09 0.02 0.14 0.05

TA49 93.5 82.5 54.62 92.04 90.00 15.00 132.00 31.09 98.29 70.00 18.00 330.00 104.13

BS 15.27 15 4.78 15.00 14.00 6.00 23.00 4.66 16.14 17.00 5.00 21.00 5.43

AG 18.7 15 9.69 19.30 15.00 10.00 51.00 10.34 16.71 15.00 9.00 29.00 7.43

Categorical independent variables Proportion of banks coded 1 Proportion of banks coded 1 Proportion of banks coded 1


ML (Big 4auditor) 77 82.6 71.4


measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the debt equity ratio. TA denotes total assets, BS denotes the

number of board members, AG denotes age measured as numbers of years from incorporation, RMU denotes presence of a risk management unit, ML denotes the presence of a multinational

linked auditor.


32Table 9.2(Panel E): Descriptive statistics year 2010 (N=30)

236


Dependent and continuous independent variables Mean Median Std.

Dev.


Dev.


Dev.

RDI 0.76 0.8 0.11 0.79 0.81 0.60 0.87 0.08 0.67 0.70 0.37 0.81 0.15

BI 0.05 0.05 0.04 0.06 0.06 0.00 0.13 0.04 0.03 0.05 0.00 0.08 0.03

ACI 0.19 0.2 0.13 0.22 0.20 0.00 0.33 0.12 0.11 0.00 0.00 0.33 0.14

RC 2.67 3 1.35 2.96 3.00 1.00 6.00 1.33 1.71 1.00 1.00 3.00 0.95

DE 0.11 0.09 0.12 0.11 0.09 0.05 0.71 0.13 0.08 0.10 0.02 0.17 0.06

TA50 120.37 106.5 82.61 113.74 116.00 15.00 199.00 41.07 142.14 91.00 18.00 502.00 161.50

BS 14.77 14.5 4.88 14.48 14.00 6.00 23.00 4.83 15.71 17.00 5.00 20.00 5.28

AG 19.77 16 9.63 20.39 16.00 12.00 52.00 10.27 17.71 16.00 10.00 30.00 7.43

Categorical independent variables Proportion of banks coded 1 Proportion of banks coded 1 Proportion of banks coded 1



Legend: Where, RDI denotes Risk Disclosure Index, BI denotes board independence measured as proportion of independent directors on the board. ACI denotes Audit Committee

Independence measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the debt equity ratio. TA denotes total assets, BS

denotes the number of board members, AG denotes age measured as numbers of years from incorporation, RMU denotes presence of a risk management unit, ML denotes the presence of a

multinational linked auditor.


33Table 9.2(Panel F): Descriptive statistics year 2011 (N=30)

237



Mean Median Std.

Dev.


Dev.


Dev.

RDI 0.77 0.81 0.11 0.80 0.83 0.65 0.87 0.07 0.69 0.72 0.37 0.83 0.16

BI 0.07 0.06 0.06 0.07 0.07 0.00 0.25 0.05 0.06 0.06 0.00 0.20 0.07

ACI 0.2 0.2 0.13 0.22 0.20 0.00 0.33 0.12 0.16 0.20 0.00 0.33 0.16

RC 2.77 3 1.38 3.04 3.00 1.00 6.00 1.36 1.86 1.00 1.00 3.00 1.07

DE 0.07 0.09 0.3 0.12 0.09 0.05 0.71 0.13 0.11 0.10 1.43 0.18 0.58

TA51 118.27 106.5 85.43 114.00 116.00 15.00 199.00 43.52 132.29 91.00 15.00 502.00 167.43

BS 14.77 14.5 4.88 14.48 14.00 6.00 23.00 4.83 15.71 17.00 5.00 20.00 5.28

AG 20.77 17 9.63 21.39 17.00 13.00 53.00 10.27 18.71 17.00 11.00 31.00 7.43

Categorical independent variables Proportion of banks coded

1





measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the debt equity ratio. TA denotes total assets, BS denotes the

number of board members, AG denotes age measured as numbers of years from incorporation, RMU denotes presence of a risk management unit, ML denotes the presence of a multinational

linked auditor.


34Table 9.2(Panel G): Descriptive statistics year 2012 (N=30)

238

9.4 Univariate statistics: ANOVA and Chi-Square tests

9.4.1 Significance of mean over time: ANOVA

To compare the significance of mean values across the period 2006-2012, Table 9.3

provides the results of an ANOVA analysis.

Predictor Variables

BI ACI RC DE TA RMU BS ML AG

F 2.047 .533 .533 .535 .366 .675 1.724 .052 2.091

Sig .074* .587 .587 .750 .694 .510 .132 .998 .169

Legend: Where, BI denotes board independence measured as proportion of independent

directors on the board. ACI denotes Audit Committee Independence measured as

proportion of independent directors on the audit committee, RC denotes number of risk

committees, DE denotes the debt equity ratio. TA denotes total assets, RMU denotes

presence of a risk management unit, BS denotes the number of board members, ML

denotes the presence of a multinational linked auditor, AG denotes age measured as

numbers of years from incorporation. ***highly significant at 1% level,**significant at

5% level* moderately significant at 10%

Table 9.3 compares the mean values for bank characteristic variables. Table 9.3 reveals

that none differs significantly from the mean value (p>0.100) except BI (p=.074).

Appendix 9.1 presents the post hoc Tukey p values for each year. The significance level

varies in sample years over the sample period for the predictor variables.

9.4.2 Islamic versus Non-Islamic banks-Continuous variables

To compare the characteristics of Islamic versus Non-Islamic banks, t tests were

performed. Table 9.4 reveals that the mean values of all continuous dependent and

independent variables [Risk Disclosure Index (RDI), board independence (BI), audit

committee independence (ACI), risk committee (RC), debt to equity ratio (DE)] are

significantly different between the two types of banks (at p<0.05 level). However, the

control variables, board size (LnBS) and age (LnAG) are not significantly different.

35Table 9.3: ANOVA by year (2006-2012)

239

t-statistic p-value Mean

Difference

Std. Error

Difference

RDI 4.30 0.00 0.13 -0.02

BI 3.09 0.00 0.02 0

ACI 2.79 0.01 0.06 0.01

RC 2.76 0.01 0.61 0.54

DE 2.20 0.03 0.05 -0.13

LnTA 2.12 0.00 -5.57 -41.74

LnBS 1.08 0.28 -1.36 -0.93

LnAG 1.44 0.15 2.57 3.04

Legend: t tests of difference in means for continuous variables (Non-Islamic [N=161 or

77%] and Islamic [N=49 or 23%]) as reported in Table 9.3.

Where, RDI denotes Risk Disclosure Index, BI denotes board independence measured as

proportion of independent directors on the board. ACI denotes Audit Committee Independence

measured as proportion of independent directors on the audit committee, RC denotes number of

risk committees, DE denotes the debt equity ratio. TA denotes total assets, BS denotes the

number of board members, AG denotes age measured as numbers of years from incorporation,

RMU denotes presence of a risk management unit, ML denotes the presence of a multinational

linked auditor.

9.4.3 Islamic versus Non-Islamic banks - Categorical variables

Both parametric and non-parametric tests were performed for categorical variables

reported in Table 9.3 to identify whether the presence of a multinational linked auditor

and a risk management unit have an association with the overall Risk Disclosure Index.

t-tests were conducted to compare the Risk Disclosure Index for banks with and without

a multinational linked auditor (ML) and banks with and without risk management units

(RMU). Table 9.5 presents the RMU and ML matrix for further analysis.

Table 9.4: t tests for continuous variables

240

Full observation (N=210) Non-Islamic

(N=161)

Islamic (N=49)

Pearson

Chi-

Square

Sig.

(2tailed)

Eta Squared

and Effect

size52

*

Pearson

Chi-

Square

Sig.

(2tailed)

Pearson

Chi-

Square

Sig.

(2tailed)

RMU 112.466 .000 0.314 and

Large effect

96.30 .000 43.99 .06

ML 98.566 .000 0.038 and

Small effect

72.34 .000 42.17 .08

Legend: Where, RMU denotes presence of a risk management unit, ML denotes the

presence of a multinational linked auditor

Table 9.5 and Appendix 9.2 show the univariate statistics for categorical variables

across the sample period for pooled data and the effect size of differences in categorical

variables (RMU and ML). The Chi-square (112.466) for RMU is significant (p<0.05)

with a large size effect (eta squared=0.314). This goes with predicted expectation that

banks with a risk management unit score higher in the Risk Disclosure Index than banks

without. The Chi-square (98.566) for ML is significant (at p<0.001 level) and the

magnitude of the difference is small (eta squared=0.038). That is, multinational linked

auditors have an association with the Risk Disclosure Index, but with a small size effect.

Additionally, the Chi-square for Non-Islamic banks are highly significant (at p<0.001

level) for both RMU and ML however, for Islamic banks these two variables (RMU and

ML) are moderately significant (at p<0.10 level).

9.5 Bivariate analysis

In this section, various tests are used to measure the relationship among the variables.

These include Pearson product –moment correlation coefficients, and t tests. Firstly, the

Pearson product-moment correlation coefficients are calculated to test the correlations

between the dependent variable (Risk Disclosure Index) and the predictors and between

the predictors (board independence, audit committee independence, number of risk

52

*Appendix 9.2

36Table 9.5: Pearson Chi-Square test for categorical variables

241

committees, debt to equity ratio, total assets, presence of risk management unit, board

size, multinational linked auditor, age), transformed as appropriate.

Multicollinearity as a statistical problem is one of the potential issues in multivariate

analysis. Multicollinearity occurs when there are a high correlations between the

independent variables. Multicollinear variables can create misleading results.

Correlation coefficients between independent variables of 0.8 or 0.9 are often the

benchmark for multicollinearity concerns (Hair et al 1998, Tabachnik & Fidell (2001).

Table 9.6 shows the results for the tests of correlation.

242

RDI BI ACI RC DE LnTA RMU LnBS ML LnAG Islamic

BI .335**

1.00

ACI .299**

.308**

1

RC .385**

.305**

.349**

1

DE .033 -.107 -.117 .079 1

LnTA .540**

.152* .203

** .215

** .120 1.00

RMU .562**

.257**

.423**

.478**

-.091 .310**

1

LnBS .157* -.078 .076 .037 .150

* .267

** .104 1

ML .226**

.147* .068 -.096 -.127 .096 .113 -.300

** 1

LnAG .195**

.053 -.094 -.002 -.131 .347**

-.019 -.012 .175* 1

Islamic -.285**

-.212**

-.190**

-.190**

-.151* -.145

* -.096 .075 -.151

* -.099 1

Legend: Where, BI denotes board independence measured as proportion of independent directors on the board. ACI denotes Audit Committee

Independence measured as proportion of independent directors on the audit committee, RC denotes number of risk committees, DE denotes the

debt equity ratio. TA denotes total assets, RMU denotes presence of a risk management unit, BS denotes the number of board members, ML

denotes the presence of a multinational linked auditor, AG denotes age measured as numbers of years from incorporation. Islamic and Non-

Islamic are indicator variables measured as 1 for Non-Islamic and 0 for Islamic banks. *highly significant at 1% level**significant at 5%

level*** moderately significant at 10%

37Table 9.6: Pearson’s Correlations Pooled Data (2006-2012) (N=210)

243

Table 9.6 reports that the highest coefficient correlation is 0.562 for the presence of a

risk management unit (RMU)53

with the dependent variable Risk Disclosure Index.

Therefore, Table 9.6 provides no indication that an unacceptable level of

multicollinearity concerns is present.

Board independence (BI), number of risk committees (RC) and audit committee

independence (ACI) as proxies for risk governance are correlated positively and are

statistically significant at p<0.05 level. The direction of this correlation is consistent

with Hypotheses H2, H3 and H454

.The correlation coefficients for BI and RC with RDI

are below 0.4.

The debt to equity ratio (DE) and RDI are positively related, however there is no

statistical significance across the period (2006-2012). The predicted direction of the

correlation is not in accordance with that hypothesised for DE, given the a priori

expectation from neo-institutional theory. Similar results were found in previous studies

(Abraham & Cox 2007; Linsley & Shrives 2005a; Mohobbot 2005).

Log of total assets (LnTA) and presence of a risk management unit (RMU) are

positively and statistically significantly correlated with RDI at p<0.05 level. The values

of correlation coefficients are higher for LnTA (0.540) and RMU (0.562) compared to

other predictors. The directionality of these correlations is consistent with Hypotheses

53

Risk Management Unit is not included amongst the 147 items in the Risk Disclosure Index.

54


disclosure. H3: The number of independent directors on the audit committee is associated positively with

the extent of risk disclosure. H4: The number of risk committees is positively associated with the extent of

risk disclosure.

244

H655

and H756

. The strength of correlation between control variables (LnBS, ML and

LnAG) and RDI is below 0.3.


This Chapter presents a discussion of descriptive statistics, t- tests, ANOVA and post

hoc Tukey analysis relating to the dependent variable and possible determinant and

control variables of full sample and sub-sample (Islamic and Non-Islamic). The study

provides evidence that non-conventional banks provide less risk-related disclosures

compared with conventional or Islamic banks. The ANOVA and Chi-square tests

compare the mean value over time and the significance of categorical variables

respectively. The correlation coefficients suggest the association between the predictor

variables is not at a level that causes multicollinearity concerns. The next Chapter

reports the statistical analysis and the testing of the Hypotheses using multiple

regression analysis.

55

H6: Mimetic isomorphism of larger banks influences smaller banks to provide more risk disclosure 56

H7: Normative isomorphism is positively associated with the extent of risk disclosure.

246

CHAPTER 10: Factors Underlying Risk Disclosure: Multivariate

Statistics

10.1 Introduction

To examine the association between potential determinants and the Risk Disclosure

Index, this Chapter reports the multivariate testing of the Hypotheses developed in

Chapter 5. The statistical analysis focuses on the independent and control variables

hypothesised to be associated with risk disclosure patterns. The tests involve use of

Ordinary Least Square (OLS) regression modelling with the Risk Disclosure Index as

the dependent variable in relation to the possible predictor variables.

As explained in Chapter 6, the present study examines the relationship between six

independent variables (board independence, audit committee independence, number of

risk committees, debt to equity ratio, log of total assets and presence of a risk

management unit), control variables (log of board size, presence of a multinational

linked auditor, and log of age since incorporation), and the dependent variable (Risk

Disclosure Index), across the period 2006-2012. The bivariate statistics for the

dependent, independent and control variables reported in the previous Chapter (Chapter

9) discussed the correlations between these variables in detail. This Chapter reports the

outcome of examination of interrelationships between the variables. Thus, this Chapter

discusses how well the theoretical discussion in Chapter 5 fits with the outcomes of

modelling the hypothesised Risk Disclosure Index determinants.

This Chapter is organised as follows: section 10.2 presents the multivariate regression

model to examine the association of the predictors with the Risk Disclosure Index,

section 10.3 presents normality and multicollinearity checks for regression assumptions.

Section 10.4 presents the robustness of findings in relation to the empirical tests.

Section 10.5 reports the sensitivity findings and section 10.6 presents the robustness of

findings in relation to the empirical tests. Section 10.7 provides results for analysis of

the association between the change in Risk Disclosure Index and the change in predictor

variables between sample periods. Section 10.8 discusses the findings and section 10.9

concludes the Chapter. A follow up table concludes the triangulation of the results from

247

quantitative and qualitative findings of this study and the Chapter concludes in section

10.10. Figure 10.1 provides an overview of this Chapter.

10.2 Multivariate regression model

The multivariate regression model developed to test the association of the independent

and control variables with the dependent variable was presented in Chapter 6. As

discussed in Chapter 6, the dataset used in this study can be described as cross sectional

time series or balanced panel, however, the Hausman test statistics failed to reject the

null of no systematic differences in coefficients between pooled OLS and panel fixed

effects. Hence, a pooled OLS robust regression model is estimated using the Risk

Disclosure Index (RDI) as the dependent variable and clustering on bank identity.

The following multivariate regression model is developed (in Chapter 6) to test the

association between Risk Disclosure Index and the independent and control variables

and is repeated here for convenience and Table 10.1 includes the variable definitions.

+ + + + + + + +

+ + YEARit +


Introduction (10.1) Regression model

(10.2) Normality and

multicollinearity

(10.3)

Hypothesis Testing

(10.4)

Change in

disclosure (10.7)

Robustness check

(10.6) Sensitivity Analysis

(10.5)

Chapter conclusion

(10.10)

Discussion (10.8)

248

Variables Code Expected

Sign

Measurement

Dependent

variable

Risk Disclosure Index score (refer Chapter 6)

for bank i in year t,

Independent

variables

+ Board Independence (proportion of

independent directors) for bank i in year t,

+ Audit committee independence (proportion of

independent members) for bank i in year t,

+ Number of risk committees for bank i in year t,

+ Debt to equity ratio for bank i in year t,

+ Log of Total Assets for bank i in year t,

+ Indicator for Risk Management Unit for bank i

in year t, (1=presence of, otherwise 0)

Control

variables

+ Log of Board Size for bank i in year t,

+ Indicator for multinational linked audit firm for

bank i in year t, (1=Big 4 auditor, otherwise 0)

+ Log of Age of bank since incorporation i in

years t,

Stochastic error

10.3 Normality and multicollinearity

As multiple regression makes a number of assumptions, testing the normality, linearity

and reliability of the data is required. Before going to regression analysis, these

concerns are discussed in detail in the next sub-section.

10.3.1 Normality

Normality means that the data is sampled from a normally distributed population (Allen

& Bennett 2010). Skewness and kurtosis assess the degree of normality. The skewness

value indicates the ‘symmetry of the distribution’ whereas kurtosis indicates the

‘peakiness’ of the distribution (Pallant 2011, p.57). Absolute values of skewness and

38Table 10.1: Variable Definitions

249

kurtosis exceeding 2 and 7 respectively are considered moderately non-normal

distribution (West, Finch & Curran 1995). In addition, Kline (2005) recommended an

absolute kurtosis value greater than 10.0 is indicative of problematic non-normality and

values greater than 20.0 may suggest a serious deviation from normality. Morgan et al.

(2007) suggested skewness and kurtosis statistics between -1.0 to 1.0 are acceptable.

Table 10.2 presents the skewness and kurtosis statistics for the pooled data for the

dependent, control and independent variables.

Table 10.2 indicates the standard error of skewness is 0.181. Hence, twice the standard

error of skewness is (2*.181) 0.362. The range is +0.362 to -0.362 to check whether the

value for skewness falls within this range. As the values in Table 10.2 are within this

range, it can be considered that the distribution is normal. As total assets, board size and

age are skewed to the left, the natural log of these three items is computed. The standard

error of kurtosis is 0.36. Hence, twice the standard error of kurtosis is (2*0.36). The

normality range is therefore +0.72 to -0.72. Table 10.2 indicates that the values of

kurtosis are within this range.

250

Dependent, Independent and Control variables

RDI BI ACI RC DE TA RMU BS ML AG

Skewness -0.266 0.352 -0.026 0.336 -0.336 0.153 -0.331 -0.316 -0.316 0.315

Std. Error 0.181 0.181 0.181 0.181 0.181 0.181 0.181 0.181 0.181 0.181

Kurtosis 0.606 0.716 0 .255 0.684 0.651 0.098 0.463 0 .716 0.004 -0.649

Std. Error 0.360 0.360 0.360 0.360 0.360 0.360 0.360 0.360 0.360 0.360

Legend: Where, RDI denotes Risk Disclosure Index, BI denotes board independence measured as proportion of independent directors on

the board. ACI denotes Audit Committee Independence measured as proportion of independent directors on the audit committee, RC

denotes number of risk committees; DE denotes the debt equity ratio. TA denotes total assets, BS denotes the number of board members,

ML denotes the presence of a multinational linked auditor, AG denotes age measured as numbers of years from incorporation, RMU

denotes presence of a risk management unit.

39Table 10.2: Normality analysis for pooled data (2006-2012) (N=210)

251

10.3.2 Multicollinearity

A lack of multicollinearity concerns is one of the assumptions of multiple regression

models. Problematic levels of multicollinearity affect the behaviour of individual

predictors and coefficient estimates vary in calculation. The Pearson’s correlations

provided in the bivariate statistics in Chapter 9 (Table 9.6) shows no problematic

multicollinearity concern (all correlations are below 0.7) (Hair et al. 2010; Pallant

2010). A collinearity diagnostic table is presented in Table 10.3 and further explains

that multicollinearity is not a concern. The Tolerance statistic in Table 10.3 shows that

the variability for each independent variable exceeds the cut-off point (less than .10).

Table 10.3 further reveals that that the Variance Inflation Factor (VIF) is well below the

cut-off point (above 10). Hence, multicollinearity is not at levels likely to cause

concern. However, for transparency the highest VIF is disclosed for each regression.

252

Legend: VIF* denotes Variance Inflation Factor. BI denotes board independence measured as proportion of independent directors

on the board. ACI denotes Audit Committee Independence measured as proportion of independent directors on the audit committee,

RC denotes number of risk committees; DE denotes the debt equity ratio. LnTA denotes log number of total assets, RMU denotes

presence of a risk management unit, LnBS denotes the log number of board members, ML denotes the presence of a multinational

linked auditor, LnAG denotes log age measured as numbers of years from incorporation.

40Table 10.3: Collinearity statistics for pooled data (2006-2012) (N=210)

Independent and Control variables

BI ACI RC DE LnTA RMU LnBS ML LnAG

Tolerance 0.820 0.730 0.652 0.868 0.669 0.621 0.793 0.799 0.780

VIF* 1.221 1.371 1.534 1.152 1.495 1.611 1.261 1.252 1.282

253

10.4 Multiple regression results: Hypothesis testing

As discussed in the previous section, prior to running the regression, the

multicollinearity of the explanatory variables is tested. In addition, the White (1980)

heteroscedasticity test statistics are reported for the regressions. Table 10.4 reports the

regression results estimating the factors associated with the Risk Disclosure Index for

30 banks per year over a period of seven years from 2006 to 2012. The regression

specification reported in column 1 includes Hypothesis and control variables included in

this study. Additionally, column 2 takes account of Non-Islamic (banks) as a control

variable with other Hypothesis and control variables.

The adjusted coefficient of determination (adjusted R2) indicates that 55 per cent (both

columns) of the variation of the dependent variable is explained by the variation in the

independent variables and the model is highly significant (at p<0.001 level). The first

column in Table 10.4 reveals that the presence of a risk management unit (RMU)57

makes the highest contribution to the dependent variable and age (LnAG) makes the

least unique contribution to the dependent variable. In addition, the regression provides

evidence for acceptance of Hypotheses H2, H4, and H7. That is, a higher number of

independent directors on the board are expected to be associated positively with a

higher extent of risk disclosure (H2) and this result is supported, the number of risk

committees is positively associated with the extent of risk disclosure (H4) and risk

management unit (H7) is positively associated with the extent of risk disclosure (H6).

However, H3: there is a positive association between the proportion of independent

directors on the audit committee and the extent of risk disclosure and H5: coercive

isomorphic pressures are positively associated with the extent of risk disclosure, are not

supported from the empirical findings in this study. The second column in the Table

10.4 reveals that the presence of risk management unit (RMU) and Non-Islamic banks

make the strongest contribution to explaining the dependent variable. In addition, higher

numbers of independent directors on the board are positively associated with a higher

extent of risk disclosure. The number of risk committees is positively associated with

extent of risk disclosure in column one, however, not in column

57

The presence of a Risk Management Unit is not included amongst the 147 items in the Risk Disclosure

Index.

254

Legend: RDI is dependent variable and denotes Risk Disclosure Index. The predictors

BI denotes board independence measured as proportion of independent directors on the

board. ACI denotes Audit Committee Independence measured as proportion of

independent directors on the audit committee, RC denotes number of risk committees.

DE denotes the debt equity ratio, LnTA denotes log of total assets, RMU denotes

presence of a risk management unit, LnBS denotes log number of board members, ML

denotes the presence of a multinational linked auditor and LnAG denotes age measured

as log numbers of years from incorporation. White (1980) heteroscedasticity consistent

coefficients are reported. ***, **, and * denote the level of significance at 1%, 5% and

10%, respectively. t-statistics are reported in brackets.

41Table 10.4: Pooled OLS robust regression results for Risk Disclosure

Index with a sample of 210 bank- years 2006-2012

Variables (1)

(2)

Constant -0.113 -1.913***

(-1.452) (-3.650)

BI 0.630*** 0.554**

(2.834) (2.464)

ACI 0.002 -0.035

(0.034) (-0.461)

RC 0.116** 0.013

(1.974) (1.641)

DE 0.067 0.027

(0.816) (0.312)

LnTA 0.079*** 0.085***

(3.451) (3.553)

RMU 0.135*** 0.135***

(5.487) (5.516)

LnBS 0.048* 0.050**

(1.902) (1.983)

ML 0.078*** 0.067***

(3.015) (2.721)

LnAG 0.024 0.0173

(1.203) (0.815)

Non-Islamic

Year Dummies

-

Yes

0.062***

(3.004)

Yes

R-squared 0.585 0.593

Adj. R-squared

F-Stat.

0.553

27***

0.551

27***

White Stat.(p-value)

No. of Observations

Highest VIF

0.145

210

1.66

0.114

210

1.96

255

10.4.1 Agency theory and Risk Disclosure Index Determinants: Board

independence (BI) and number of risk committees (RC) are significant

As argued in Chapter 5, which discusses the theoretical perspective underpinning the

research, it is argued that the monitoring mechanisms for risk governance through board

independence, audit committee independence and the presence of a risk committee, can

efficiently use risk information in the organisation to minimise information asymmetry

and risk bearing cost. Of the three monitoring mechanisms for risk governance

discussed in Chapter 5, board independence and the number of risk committees reveal

significance (at the 1 per cent and 5 per cent levels respectively) in column one, while

audit committee independence reveals the expected sign (a positive coefficient) but is

not significant in the regression model.

It was envisaged that a higher percentage of independent board members would

positively influence risk disclosure. Consistent with Aebi, Sabato and Schmid (2012);

Baek, Johnson and Kim (2009); Beretta and Bozzolan (2004); Cheng and Courtenay

(2006), Table 10.4 reports that board independence (BI) is a significant predictor of the

Risk Disclosure Index. Board independence is statistically positively significant in

regression model, leading to acceptance of Hypothesis H258

(consistent with agency

theory tenets). A higher percentage of independent board members seem to influence

risk disclosure positively.

The coefficient for the number of risk committees (RC) is statistically significant in

modelling the Risk Disclosure Index. Providing support for agency theory doctrines,

H459

is accepted, indicating that the greater the number of risk committees that banks

has, the more banks disclose their risk information. Consistent with Mongiardino and

Plath (2010), this finding suggests implicitly that risk committees are able to assess the

risk profile through their involvement in monitoring assets and liabilities. Aebi, Sabato

and Schmid (2012) also found the presence of risk committees to be associated with

banks’ performance during the financial crisis period of 2007-2008. Table 10.4 further

58


disclosure 59

H4: The number of risk committees is positively associated with the extent of risk disclosure.

256

presents the coefficient for the number of risk committees (RC) as not statistically

significant in the model.

10.4.2 Association of institutional isomorphism and Risk Disclosure Index:

mimetic isomorphism and normative isomorphism are significant

As discussed in Chapter 5, institutional isomorphic changes (coercive, mimetic and

normative isomorphism) are expected to be associated with risk disclosure. Hypotheses

H560

, H661

and H762

are developed based on institutional isomorphism concepts.

Of the three institutional isomorphism proxies, total assets (LnTA) and risk

management unit (RMU) presence show a strong association with the Risk Disclosure

Index, while the debt to equity (DE) ratio shows the expected sign but is not significant.

This finding is curious given that bank depositors are an influential group of

stakeholders. A possible reason for this finding is that bank depositors do not demand

risk disclosure information. However, this is merely conjecture at this stage. It is

envisaged that the best way to find some possible explanation for this finding is through

direct communication with representatives from the banks included in this study

(Discussed in Chapter 8)63

.

The regression results show that coefficient estimates for total assets (LnTA) are

positive and statistically significant (at p<0.001 level), suggesting that asset size

significantly positively influences banks in disclosing their risk exposures. This finding

complements the mimetic isomorphism theory tenets (DiMaggio & Powell 1983) and

the qualitative findings from Chapter 8 and is consistent with studies by Beretta and

Bozzolan (2004), Linsley, Shrives and Crumpton (2006) and Lopes and Rodrigues

(2007) suggesting that banks with more assets disclose more risk exposures. The

60

H5: Coercive isomorphic pressures are positively associated with the extent of risk disclosure. 61

H6: Mimetic isomorphism of larger banks influences smaller banks positively to provide more risk

disclosure. 62

H7: Normative isomorphism is positively associated with the extent of risk disclosure.

63

As discussed in Chapter 8, depositors are more interested in profitability information rather risk. In

addition to that, lack of knowledge also limits their understanding about the importance of risk

assessment in annual reports.

257

theoretical discussion leads to the Hypothesis in Chapter 5 that mimetic isomorphism in

larger banks has an influence on the extent of risk reporting by smaller banks. However,

the influence of larger banks on smaller banks is not testable empirically, therefore, the

discussion within Chapter 8 (An Exploration of Banks’ Risk Disclosure Practices and

their Determinants in Bangladesh: Qualitative Analysis of Interview Data) provides

support for the mimetic isomorphism (using qualitative data).

The coefficient estimate for the presence of a risk management unit (RMU) is positive

and makes the strongest contribution of the predictor variables to explaining the

dependent variable. The level of statistical significance indicates that the presence of a

risk management unit (RMU) in banks can play a vital role in improving the level of

risk disclosure in financial reporting.

10.4.3 Control variables: multinational linked audit firm (ML) and board

size (LnBS) are significant

The coefficients for the control variables have the expected signs. Of the three control

variables, the presence of a multinational linked audit firm (ML) and board size (LnBS)

are significant at one per cent and 10 per cent respectively. ML has a strong association

with the Risk Disclosure Index in this multivariate analysis. The finding suggests that

banks having multinational linked audit firms communicate more risk information than

those without such auditors. The bivariate and multivariate statistics show that board

size (LnBS) is weakly significant at the 10 per cent level. Another control variable age

(LnAG) is significant in bivariate statistics however insignificant in the multivariate

regression model.

10.5 Sensitivity analysis

Sensitivity analysis is conducted to check the robustness of the main findings from

analysis of the model presented in section 10.5 (see Table 10.5). Sensitivity analysis is

applied to determine the extent to which the independent variables used in the main

multiple regression analysis is sensitive to different measures of the same variables. The

regression specification reported in column 1 includes Hypothesis and control variables

258

included in this study. Additionally, column 2 takes account of Non-Islamic (banks) as a

control variable with other Hypothesis and control variables.

First, in the main regression model (see Table 10.4), coercive isomorphism (CI) is

measured as the debt to equity ratio. CI is not significant in the main regression model.

For sensitivity analysis, CI is measured as the ratio of total assets to total deposits (AD).

Table 10.5 shows the regression model results for sensitivity analysis using total assets

to total deposits as a proxy to recalculate coercive isomorphism. The main regression

model shows the debt to equity ratio is insignificant with a positive coefficient (see

Table 10.4). In sensitivity analysis, assets to deposits (AD) is marginally significant at

the 1 per cent level. The findings show assets to deposits (AD) is weakly significant

despite the insignificance of debt to equity (DE) in the main regression model.

However, the adjusted R2 (51 per cent) falls compared to the main regression (55 per

cent).

Second, board independence is calculated as a proxy to measure risk governance in the

main analysis (see Table 10.6). In sensitivity analysis, board independence is

remeasured with the number of board meetings. Table 10.6 reveals that the number of

board meetings is positively significant as was board independence in the main

regression, apart from the level of significance (board meeting is significant at 5% level

however, board independence is significant at 1% level). The adjusted R2 (49.2 per cent)

goes down compared to the main regression (55%). In conclusion, a different measure

of risk governance does seem to make a difference in hypothesis testing.

259

(Coercive isomorphism= Total assets/total deposits)

Variables (1) (2)

Constant -0.122

(-1.572)

-0.115

(-1.351)

BI 0.583***

(2.604)

0.341***

(1.504)

ACI -0.037

(-0.510)

-0.148

(-0.317)

RC 0.016*

(1.935)

0.116*

(1.334)

AD 0.105*

(1.696)

0.144**

(2.096)

LnTA

0.025*

(1.837)

0.035*

(1.337)

RMU 0.122***

(4.960)

0.112***

(3.860)

LnBS 0.032

(1.184)

0.122

(1.144)

ML 0.080***

(3.349)

0.070***

(2.699)

LnAG -0.001

(-0.087)

-0.071

(-0.481)

Non-Islamic

- 0.152***

(2.691)

Year Dummies Yes

Yes

R-squared

Adj. R-squared

0.533

0.518

0.582

0.537

F-Stat. 22*** 26***


Number of observation

Highest VIF

0.134

210

1.67

0.121

210

1.86

Legend: RDI is dependent variable and denotes Risk Disclosure Index. The predictors BI

denotes board independence measured as proportion of independent directors on the board. ACI

denotes Audit Committee Independence measured as proportion of independent directors on the

audit committee, RC denotes number of risk committees, AD denotes total assets to total

deposits, LnTA denotes log number of total assets. RMU denotes presence of a risk

management unit, LnBS denotes log number of board members, ML denotes the presence of a

multinational linked auditor and LnAG denotes age measured as log numbers of years from

incorporation. White (1980) heteroscedasticity consistent coefficients are reported. ***, **, and

* denote the level of significance at 1%, 5% and 10%, respectively. t-statistics are reported in

brackets.

42Table 10.5: Pooled OLS regression results for the Risk Disclosure Index

with a sample of 210 bank years 2006-2012

260

(Board Independence= Board Meeting)

Variables (1) (2)

Constant 0.139

1.821

0.091

0.711

BM 0.128

1.539**

0.105

1.411**

ACI 0.058

0.835

0.138

0.714

RC 0.087

1.858**

0.181

1.947**

DE 0.123

1.142

0.011

1.171

LnTA 0.510

4.526*

0.480

3.221*

RMU 0.145

2.412**

0.114

1.312

LnBS 0.156

2.762***

0.142

1.762*

ML 0.164

2.517***

0.171

1.411

LnAG 0.163

2.562**

0.153

1.682*

Non-Islamic

- 0.121***

(2.701)

Year Dummies Yes

Yes

R-squared

Adj. R-squared

0.519

0.492

0.431

0.412

F-Stat. 23*** 21***


Number of

observation

Highest VIF

0.134

210

1.54

0.112

210

1.31

Legend: RDI is dependent variable and denotes Risk Disclosure Index. The predictors

BM denotes board meeting measured number of board meetings. ACI denotes Audit

Committee Independence measured as proportion of independent directors on the audit

committee, RC denotes number of risk committees; DE denotes the debt equity ratio.

LnTA denotes the log number of total assets, LnBS denotes log number of board

members, LnAG denotes log number of age measured as numbers of years from

incorporation, RMU denotes presence of a risk management unit, and ML denotes the

presence of a multinational linked auditor. White (1980) heteroscedasticity consistent

coefficients are reported. ***, **, and * denote the level of significance at 1%, 5% and

10%, respectively. t-statistics are reported in brackets.

43Table 10.6: Pooled OLS regression results for Risk Disclosure Index with a

sample of 210 bank years 2006-2012

261

10.6 Robustness check

This section provides robustness checks of the results reported in Chapters 7 and 9 and

the multiple regression analyses reported in the previous section in this Chapter. This

section provides and discusses further analysis of the predictor and control variables

including use of profitability as a control variable, In addition, this section discusses

predictors and control variables hypothesised to be associated with the five major risk

types (Market, Credit, Liquidity, Operational and Equities). Robustness checks in this

section examine also the association of the Risk Disclosure Index with changes in the

predictors and control variables across the period from 2006-2012.

10.6.1 Association of Risk Disclosure Index with profitability

This section examines return on assets (ROA) as a measure for profitability in the main

regression model. Previous studies (Linsley & Shrives 2005a; Mohobbot 2005) argued

risk and return are related and better risk management companies disclose their risk

management ability to the market. Therefore, the robustness check in this section

investigates the association of the Risk Disclosure Index as the dependent variable in

relation to the independent variables (board independence, audit committee

independence, number of risk committees, debt to equity ratio, log of total assets, risk

management unit) and control variables (log of board size, multinational linked audit

firm, age and return on assets). Table 10.7 presents the regression results using return on

assets as a proxy for profitability (control variable) in the main regression model. Table

10.7 shows the adjusted R2

(51.4 per cent) falls compared to the main regression (55 per

cent). Apart from the level of significance (1, 5 or 10 per cent) this model shows the

same significant predictors (BI, RC, LnTA, RMU, LnBS, and ML). However, no

association is found between Risk Disclosure Index and profitability. Next Chapter

examines in detail the relationship between Risk Disclosure and bank performance.

262

(Profitability= ROA)

Variables (1) (2)

Constant 0.115

(1.370)

0.195

(0.113)

BI 0.636***

(2.831)

0.636*

(1.680)

ACI 0.026

(0.014)

0.001

(0.014)

RC 1.920*

(1.690)

1.020

(0.169)

DE 0.065

(0.800)

0.012

(0.710)

LnTA 0.079***

(3.311)

0.135***

(2.681)

RMU 0.136***

(5.321)

0.136

(1.170)

LnBS 0.047**

(1.990)

0.135**

(1.981)

ML 0.077***

(2.981)

0.124***

(2.681)

LnAG 0.025

(1.224)

0.214

(1.114)

ROA 0.005

(0.090)

0.112

(0.181)

Year Dummies Yes

Yes

R-squared

Adj. R-squared

0.547

0.514

0.477

0.403

F-Stat. 24*** 21***


Number of observation

Highest VIF

0.127

210

1.53

0.114

210

1.21

Legend: RDI is dependent variable and denotes Risk Disclosure Index. The predictors BI

denotes board independence measured as proportion of independent directors on the board.

ACI denotes Audit Committee Independence measured as proportion of independent

directors on the audit committee, RC denotes number of risk committees; DE denotes the

debt equity ratio. LnTA denotes log number of total assets, LnBS denotes log number of

board members, LnAG denotes log number of age measured as numbers of years from

incorporation, RMU denotes presence of a risk management unit, and ML denotes the

presence of a multinational linked auditor. ROA denotes return on assets measured as net

profit after tax divided by total assets. White (1980) heteroscedasticity consistent coefficients

are reported. ***, **, and * denote the level of significance at 1%, 5% and 10%,

respectively. t-statistics are reported in brackets.

44Table 10.7: Pooled OLS regression results for Risk Disclosure

Index with a sample of 210 bank years 2006-2012

263

10.6.2 Five types of Risk Disclosure

This section presents regression analyses of the Risk Disclosure Index broken down into

each of the five risk types (separately) with the predictors and control variables

hypothesised in this research. The multiple regression models for these five types of

Risk Disclosure Index are as follows:

+ + + + + + +

+ + + YEARit +

Where:

Dependent variable:

= Market, Credit, Liquidity, Operational and Equities Risk Disclosure Index

scores (separately) for bank i in year t, and the independent variables are as previously

used in the main regression model (discussed in section 10.2).

The regression models in this section explain the variance in each of the five types of

Risk Disclosure comprising the Index. These are Market Risk Disclosure Index

(MRDI), Credit Risk Disclosure Index (CRDI), Liquidity Risk Disclosure Index

(LRDI), Operational Risk Disclosure Index (ORDI), and Equities Risk Disclosure Index

(ERDI) of risk disclosure.

The highest correlations for Market Risk Disclosure Index, Credit Risk Disclosure

Index, Liquidity Risk Disclosure Index, Operational Risk Disclosure Index and Equities

Risk Disclosure Index are below 0.5 (Appendix 10.1 A-E). There is again no

problematic concern with multicollinearity between the independent variables in these

models.

Table 10.8 reports the predictive power of the model from the regression in the pooled

data. The Table presents the relationship between the independent variables (board

264

independence, audit committee independence, number of risk committees, debt to

equity ratio, total assets, presence of a risk management unit) and control variables

(board size, multinational linked audit firm, age) separately with each of the five types

of dependent variable (Liquidity Risk Disclosure Index, Market Risk Disclosure Index,

Operational Risk Disclosure Index, Equities Risk Disclosure Index and Credit Risk

Disclosure Index).

The variable board independence (BI) is statistically significant for Liquidity risk

(LRDI) and Equities risk (ERDI). However, audit committee independence (ACI) is not

significant for any of these regression models. These findings are consistent with the

main regression model discussed in section 10.4.

The coefficient for the number of risk committees (RC) is statistically significant only

in the specification for Liquidity risk (LRDI). This indicates that the greater the number

of risk committees, the more a bank discloses its Liquidity risk. Consistent with

Mongiardino and Plath (2010), this result suggests implicitly that risk committees are

able to assess the level of Liquidity risks through their involvement in monitoring assets

and liabilities.

265

Risks Type

Variables Liquidity

Risk Index

Market

Risk Index

Operational

Risk Index

Equities

Risk Index

Credit

Risk Index

Constant 0.242* 0.311*** -0.051 -0.220 0.097*

(1.691) (4.492) (-0.191) (-1.641) (1.930)

BI 0.226*** 0.041 0.038 0.160*** 0.043

(3.398) (0.639) (0.459) (2.688) (0.692)

ACI 0.098 0.069 0.096 0.117 0.037

(1.383) (0.984) (1.094) (1.594) (0.567)

RC 0.017*** 0.008 -0.007 0.020 -0.003

(2.681) (0.712) (-0.971) (1.342) (-0.461)

DE -0.031 -0.114*** 0.223*** 0.286*** -0.037

(-0.462) (-4.471) (3.244) (3.101) (-0.834)

LnTA 0.038** 0.041*** 0.093*** 0.115*** 0.059***

(1.995) (4.297) (4.508) (5.470) (9.053)

RMU 0.015 0.175*** 0.016 0.126*** 0.156***

(0.633) (4.542) (1.203) (2.364) (5.624)

LnBS 0.033* 0.020 -0.020 -0.025 0.039**

(1.945) (1.016) (-0.327) (-0.748) (2.589)

ML 0.105*** 0.066*** 0.144*** 0.065 0.086***

(3.321) (7.563) (2.687) (1.479) (3.589)

LnAG 0.271 0.016 .006 0.069 0.036

(4.130)*** (0.248) (0.075) (0.987) (0.556)

Adj R2 0.35 0.42 0.34 0.27 0.48

F-Stat. 11.91*** 12.63*** 9.36*** 8.12*** 15.80***

Year Dummies Yes Yes Yes Yes Yes

White Stat. (p-value) 16.40

0.82

12.23

0.76

31.95

0.19

6.31

0.38

31.54

0.20

45Table 10.8: Pooled OLS regression results for five types of risks with a sample of 210 bank years 2006-2012

266

No. of Observations (N)

Highest VIF

210

1.53

210

1.68

210

1.78

210

2.10

210

1.84

Legend: RDI is dependent variable and denotes Risk Disclosure Index. The predictor BI denotes board independence measured as proportion of

independent directors on the board. ACI denotes Audit Committee Independence measured as proportion of independent directors on the audit

committee, RC denotes number of risk committees; DE denotes the debt equity ratio. LnTA denotes log total assets, RMU denotes presence of a risk

management unit, LnBS denotes log number of board members, ML denotes the presence of a multinational linked auditor and LnAG denotes age

measured as log numbers of years from incorporation. White (1980) heteroscedasticity consistent coefficients are reported. ***, **, and * denote the

level of significance at 1%, 5% and 10%, respectively. t-statistics are reported in brackets.

267

The coefficient for the debt to equity ratio is highly significant (at p<0.001 level) in

specifications for Market, Operational and Equities risk. However, its negative sign in

the specification for Market risk indicates that banks with higher debt to equity ratios

are less likely to disclose Market risk exposures, while its positive sign in specifications

for Operational and Equities risk indicates that banks depending on higher debt

financing are more likely to disclose more Operational and Equities risks. This reflects

implicitly the power of creditors in encouraging disclosure of operational and equities

risks. This finding complements the mimetic isomorphism theory tenets (DiMaggio &

Powell 1983) and is consistent with empirical evidence by Beretta & Bozzolan (2004);

Linsley, Shrives & Crumpton (2006) and Lopes & Rodrigues (2007).

The regression results show that the coefficient estimates of the natural logarithm of

total assets (LnTA) are positive and statistically significant in all regressions, suggesting

that asset size is significantly positively associated with banks disclosing their various

types of risk exposures. Specifically, this result is consistent with Beretta and Bozzolan

(2004), Linsley, Shrives and Crumpton (2006) and Lopes and Rodrigues (2007) and

suggests that banks with more assets disclose more types of risk exposures; however,

larger banks disclose more Equities risk items, followed by Operational risk items,

Credit risk items, Market risk items and lastly Liquidity risk items.

The coefficient estimates for the presence of a risk management unit (RMU) for all

types of risk are positive but significant only in specifications for Market risk, Equities

and Credit risk. The lack of statistical significance for Liquidity and Operational risk

disclosure is consistent with empirical evidence provided by Aebi, Sabato and Schmid

(2012). The direction of the coefficients implies that banks with a RMU are likely to

disclose all types of risk because of normative pressures applied through

professionalisation of international disclosure standards. However, the levels of

statistical significance indicate that banks with RMUs are more likely to disclose

Market, Equities and Credit risks in that order.

The regressions results report that the coefficient for the control variable, the presence

of a multinational linked auditor (ML), is positively associated with all risk disclosure

268

types except Equities risk, while the number of board members (BS) is significantly and

positively associated with Liquidity and Credit risk. Age is significant only for

Liquidity risk disclosure.

10.7 Change in Risk Disclosure Index across the sample periods

This section examines the association between the change in Risk Disclosure Index and

the change of predictor variables between sample sub-periods. The regression model is

developed in methodology Chapter and repeated here for convenience.

The multiple regression results based on this new model are used to predict the

association between the change in the Risk Disclosure Index ( ) and change in the

value of the independent (board independence, audit committee independence, risk

committee, debt to equity ratio, total assets, risk management unit presence) and control

(board size, multinational linked audit firm and age) variables between the chosen

groups of years.

The regression model is as follows and Table 10.9 includes the variable definitions.

+ + + +

+ + + +

+ +

269


Dependent variable

Change in Risk disclosure Index for bank

i year t and t-i,


Change in Board Independence

(proportion of independent directors) for

bank i in year t,

Change in Audit committee

independence (proportion of independent

members) for bank i in year t,

Change in Number of risk committees

for bank i between year t and t-i,

Change in Debt to equity ratio for bank i

between year t and t-i,

Change in Log of Total Assets for bank i

in year t,

Change in Indicator for Risk

Management Unit for bank i in year t,

Control variables

Change in Log of Board Size for bank i

in year t,

Change in Indicator for multinational

linked audit firm for bank i in year t,

Change in Log of Age of bank since

incorporation i in year t,

Stochastic error

Appendices 10.2 to 10.5 reveal that the highest correlation for regressions

remains at less than 0.6. Multicollinearity problems between the independent and

control variables is thus deemed minimal in these change models (change in year 2006

and 2008, 2006 and 2010, 2006 and 2012, and 2010 and 2012). As mentioned in

previous Chapters, this study examined seven years (2006-2012). These periods

included GFC of 2007-2008 that raised significant concern to financial institutions. As a

result, users of financial statements acknowledged that the enhanced disclosures about

financial information could better enable the stakeholders to understand the extent of

46Table 10.9: Variable definitions

270

risk of financial instruments (IASB 2009). This study examines the association between

changes in risk disclosure as the period incorporates one of the first risk disclosures as

required by IFRS 7 since 2007. Banks in Bangladesh voluntarily adopted64

international

standards (IFRS 7 and Basel II: Market Discipline) after GFC 2007-2008 (refer Chapter

3). This study therefore examines the change in risk disclosure among pre, transition

and post reform periods. For example, pre-reform to end of GFC (2006-2008), pre-

reform to end of transition (2006-2010), pre-reform to stability (2006-2012), and post

reform (2010-2012).

The association between change in the Risk Disclosure Index and change in predictor

variables is reported in Table 10.10 with a summary of significance levels reported in

Table 10.11. These two Tables show that the intercept is significant for each change

between years. The intercept is moderately significant (at the 10 per cent level) between

years 2006 and 2008 and at the end of the transitional period (2006 and 2010), the

significance level changes to 5 per cent. This is highly significant in following the year

2006 and 2012. Table 10.12 presents the mean difference in Risk Disclosure Index

between the periods (∆2006-2008, ∆2006-2010, ∆2006-2012, and ∆2010-2012) and

there is a statistically significant differences at p<0.01 level for all these years.

The association between the Risk Disclosure Index and audit committee independence

(ACI) is significant in years 2010 and 2012. The difference implies that after the global

financial crisis, banks put more attention on audit committee independence as a higher

percentage of independent directors on the audit committee has a significant association

with the Risk Disclosure Index (see Tables 10.10 and 10.11).

Tables 10.10 and 10.11 also reveal that the predictor variable, the number of risk

committees (RC), is significant (at p<0.01 level) during GFC and after the GFC period

(2006 and 2010). The debt to equity ratio and log of total assets (LnTA) is significant

(at p<0.001 and p<0.05 level) before the GFC and during the GFC (2006 and 2008).

64

Institute of Chartered Accountants in Bangladesh adopted IFRS 7 as BFRS 7 in January 2010 and

Bangladesh Bank provided Risk Based Capital Adequacy guideline in 2010.

271

Board size (2006 and 2012) is significant at p<0.001 level and other control variables

(ML and LnAG) are insignificant throughout the models.

272

Legend: ∆2006-2008 is change in variables in year 2006 and 2008, ∆2006-2010 is change in variables in year 2006 and 2010, ∆2006-2012 is

change in variables in year 2006 and 2012, and ∆2010-2012 is change in variables in year 2010 and 2012. Change in Risk Disclosure Index

(RDI) is dependent variable. The predictors are ∆BI denotes board independence measured as proportion of independent directors on the board

47Table 10.10 Change in Risk Disclosure Index and change in predictors in pre and post GFC periods

VARIABLES ∆2006_2008 ∆2006_2010 ∆2006_2012 ∆2010_2012

∆BI -0.040 0.204* 0.758* 0.513*

(-0.070) (1.746) (1.684) (1.821)

∆ACI 0.054 -0.072 -0.016 0.313**

(0.517) (-0.392) (-0.081) (1.961)

∆RC 0.001 0.152* 0.011 0.116

(0.132) (1.681) (0.397) (-0.160)

∆DE 0.461* 0.104 0.011 0.014

(1.815) (0.146) (0.062) (-0.261)

∆LnTA 0.113*** 0.179** 0.144** -0.025

(2.813) (2.464) (2.115) (-0.212)

∆RMU 0.057** 0.003* 0.059* 0.201*

(2.050) (1.753) (1.806) (1.750)

∆LnBS -0.017 0.319*** 0.053 0.011

(-0.188) (2.803) (0.592) (-0.225)

∆ML -0.047 -0.077 0.063 -0.017

(-1.358) (-1.184) (0.656) (-0.212)

∆LnAG 0.137** 0.117 0.092 0.122

(2.131) (0.739) (0.579) (-0.721)

Constant 0.006* 0.014* 0.020** 0.241**

(1.773) (1.875) (2.197) (-1.151)

R-squared 0.576 0.665 0.691 0.553

Adj. R-squared

F-Stat.

No. of Observations

Highest VIF

0.499

17.77

60

1.36

0.664

18.79

60

1.58

0.635

17.77

60

1.35

0.493

16.17

60

1.16

273

in ∆ year. ∆ACI denotes Audit Committee Independence measured as proportion of independent directors on the audit committee in ∆ year,

∆RC denotes number of risk committees in ∆ year. ∆DE denotes the debt equity ratio in ∆ year, ∆LnTA denotes log total assets in ∆ year,

∆RMU denotes presence of a risk management unit in ∆year, ∆LnBS denotes log number of board members in ∆ year, and ∆ML denotes the

presence of a multinational linked auditor in ∆ year. ∆LnAG denotes age measured as log numbers of years from incorporation in ∆year. White

(1980) heteroscedasticity consistent coefficients are reported. ***, **, and *denote the level of significance at 1%, 5% and 10%, respectively. t-

statistics are reported in brackets.

274

∆BI ∆ACI ∆RC ∆DE ∆LnTA ∆RMU ∆LnBS ∆ML ∆LnAG

∆2006-2008 S* × × × S* HS*** MS** × × MS**

∆2006-2010 S* S* × S* × MS** S* HS*** × ×

∆2006-2012 MS** S* × × × MS** S* × × ×

∆2010-2012 MS** S* MS** × × × S* × × ×

Legend: Where ∆2006-2008 is change in variables in year 2006 and 2008, ∆2006-2010 is change in variables in year 2006 and 2010,

∆2006-2012 is change in variables in year 2006 and 2012, and ∆2010-2012 is change in variables in year 2010 and 2012. Change in

Risk Disclosure Index (RDI) is dependent variable. The predictors are ∆BI denotes board independence measured as proportion of

independent directors on the board in ∆ year. ∆ACI denotes Audit Committee Independence measured as proportion of independent

directors on the audit committee in ∆ year, ∆RC denotes number of risk committees in ∆ year. ∆DE denotes the debt equity ratio in ∆

year, ∆LnTA denotes log total assets in ∆ year, ∆RMU denotes presence of a risk management unit in ∆year, ∆LnBS denotes log

number of board members in ∆ year, and ∆ML denotes the presence of a multinational linked auditor in ∆ year. ∆LnAG denotes age

measured as log numbers of years from incorporation in ∆year. White (1980) heteroscedasticity consistent coefficients are reported.

***HS denotes highly significant at 1%; **MS denotes moderately significant 5%; *S denotes weak significance at 10%

48Table 10.11: Summary of significant variables from Table 10.10

275

∆2006-2008 ∆2006-2010 ∆2006-2012 ∆2010-2012

∆ Mean Risk Disclosure Index 0.094 0.278 0.343 0.319

t-stat 7.177 10.014 12.848 9.131

p-value 0.000 0.000 0.000 0.000

Legend: ∆2006-2008 is change in variables between year 2006 and 2008, ∆2006_2010 is change in variables between year 2006 and

2010, ∆2006_2012 is change in variables between year 2006 and 2012, ∆2010_2012 is change in variables between year 2010 and 2012.

49Table 10.12: Difference in Mean Risk Disclosure between the periods

276


This Chapter provides evidence of the predictors of the Risk Disclosure Index across the

period from 2006-2012. The five main Hypotheses are tested in this Chapter. The Table

10.4 main regression model provides evidence for accepting three Hypotheses: H2: The

number of independent directors on the board is associated positively with the extent of

risk disclosure, H4. The number of risk committees is positively associated with the

extent of risk disclosure, and H7: Normative isomorphism is positively associated with

the extent of risk disclosure. Table 10.4 also reveal the significance of Non-Islamic

indicator in regression model.

The regression results (presented in Table 10.4) show that coefficient estimates of total

assets (LnTA) are positive and statistically significant at the 1 per cent level, suggesting

that asset size significantly positively influences banks in disclosing their risk

exposures. This finding complements the qualitative evidence presented in Chapter 8 in

relation to the Hypothesis developed in Chapter 5 (Mimetic isomorphism of larger

banks influences smaller banks to provide more risk disclosure). This Hypothesis is

based on mimetic isomorphism theory tenets (DiMaggio & Powell 1983) and is

consistent with studies by Beretta and Bozzolan (2004), Linsley, Shrives and Crumpton

(2006) and Lopes and Rodrigues (2007), suggesting that banks with more assets

disclose more risk exposures.

The findings also support the theoretical tenets of agency and neo institutional

isomorphism (discussed in Chapter 5). The finding is consistent with results from

previous studies (Abraham & Cox 2007; Dobler, Lajili & Zéghal 2011; Hassan 2009;

Helbok & Wagner 2006; Taylor, Tower & Neilson 2010). The findings also suggest that

banks having larger board size and a multinational linked audit firm communicate more

about risk.

In sensitivity analysis, coercive isomorphism is measured as the ratio of total assets to

total deposits (AD) and the proxy for board independence is remeasured using number

of board meetings (BM) respectively, and both are revealed as statistically significant

277

predictors. In a robustness check, (see Table 10.8) additional regressions are estimated

to explain the variation in the five types of risk disclosure (Liquidity, Market,

Operational, Equities and Credit risk disclosure). The findings suggest that a higher

percentage of independent directors on the board are more important for disclosing

Liquidity and Equities risk. The more risk committees banks have, the more they

disclose Liquidity risks. This suggests implicitly that risk committees are able to assess

the level of Liquidity risks through their involvement in monitoring assets and

liabilities. This finding is consistent with that of Mongiardino and Plath (2010). The

debt to equity ratio is highly significant in Market, Operational and Equities risk

disclosure. This implicitly reflects the power of creditors in their invested companies

disclosing Market, Operational and Equities risks. This finding is consistent with

empirical evidence of Beretta and Bozzolan (2004); Linsley, Shrives and Crumpton

(2006); Lopes and Rodrigues (2007).

Consistent with previous studies (Beretta & Bozzolan 2004; Linsley, Shrives &

Crumpton 2006; Lopes & Rodrigues 2007) total assets (LnTA) is highly significant in

all regressions, suggesting that asset size (LnTA) positively influences banks’ risk

disclosure. However, larger banks tend to disclose more Equities risk, followed by

Operational risk, Credit risk, Market risk and Liquidity risk, in order. In addition, Table

10.8 reveals that banks with a risk management unit disclose more Market, Equities and

Credit risks than other risks.

The Chapter also details analysis that examines the association in risk disclosure

changes over time with the change in independent and control variables (see Tables

10.10-10.11). The mean difference in Risk Disclosure Index is significant in the post

GFC period. This implicitly suggests that the GFC triggered increasing demand for risk

reporting to govern accounting practices and risk disclosure. At the same time, the GFC

created significant concern over risk reporting in banking institutions.

278


This Chapter sought to investigate the factors underlying the extent of risk disclosure in

banks’ annual reports. Drawing from the literature reviewed in Chapter 4 and theoretical

discussion in Chapter 5, Hypotheses (H2, H4 and H6) have been found to be supported

as determinants of the Risk Disclosure Index together with complementary evidence in

addition to that reported in Chapter 8 regarding mimetic isomorphism. The association

between Risk Disclosure and bank performance is examined in Chapter 11.

279

CHAPTER 11: The Association between Risk Disclosure and Bank

Performance

11.1 Introduction

This Chapter presents the third Phase of a broader study that aims to investigate the

relationship between risk disclosure and bank performance. The relationship between

corporate risk disclosure and bank performance has been a major concern to the global

accounting and financial community in recent times. More specifically, the failure of a

large number of financial institutions (Lehman Brothers, Bear Stearns, Citigroup,

Merrill Lynch, HBOS) during the GFC of 2007-2008 resulted in significant impact on

the global credit market and many of the risk disclosure reforms examined in this study.

Further, it provided motivation to provide a framework for testing the value of risk

governance within financial institutions and led public policy makers to rethink the

rationale for risk governance (Aebi, Sabato & Schmid 2012; Erkens, Hung & Matos

2012; Fahlenbrach & Stulz 2011).

Previous literature argues that greater disclosure benefits investors by providing

financial data and assists them in making profitable investment opportunities (Abraham

& Cox 2007; Lajili 2009). On the contrary, some argue that greater disclosure involves

significant preparation and dissemination costs (Botosan 2004; Healy & Palepu 2001).

Additionally, banks are opaque in nature, which precludes the benefits from increased

risk disclosure (Nier & Baumann 2006).

Despite this, developing countries are characterised by corruption and gaps in

legislation and regulation (Belal, Cooper & Roberts 2013; Siddiqui 2010; Uddin &

Choudhury 2008a). Additionally, institutional pressure might create doubts about the

effectiveness of the Anglo Saxon model of corporate governance in developing

countries (Khan, Muttakin & Siddiqui 2013). This provides a research opportunity to

examine whether the doctrines of risk governance for banks that initiated in developed

countries are appropriate in developing countries.

280

As discussed in Chapter 6, bank performance is measured using two broad aspects:

bank operating performance and bank market performance. Bank operating performance

is measured as financial performance, employee efficiency, solvency efficiency and

deposit concentration. Bank market performance is measured using Tobin’s q and the

book to market ratio. This Chapter uses bank performance variables as dependent

variables (separately) (return on assets, employee efficiency, operating efficiency,

deposit concentration, Tobin’s q, and book to market ratio) and the Risk Disclosure

Index as the independent variable of interest. The extent of risk disclosure is measured

in the first Phases of this study using the Risk Disclosure Index (Chapter 7) and data for

the bank performance measures are derived from sample banks’ annual reports. This

Chapter adopts an econometric approach to testing the hypothesised relationships for 30

listed banks in each year in Bangladesh across the period 2006-2012. In the econometric

analysis, this study also controls for a number of variables (board size, board

independence, bank size, lagged performance measures, leverage, real GDP growth,

inflation rate, year effects). Following Lang and Lundholm (1996) this study uses a

lagged measure of the Risk Disclosure Index in its association with the various

measures of bank performance in order to support arguments about causal relationships.

The multivariate regression model was developed to estimate the association of the

independent and control variables with the dependent variable. Six Pooled OLS robust

regression models are estimated using the performance measures (separately) as the

dependent variable with clustering on bank identity using the White (1980) adjustment.

As discussed in Chapter 6 (Methodology), the following multivariate regression models

are developed to test the association between Risk Disclosure Index and bank

performance. The regression models are repeated here for convenience.

Models 2-5: Operating Performance = (Risk Disclosure Index score, Control variables)

Models 6-7: Bank Market Performance = (Risk Disclosure Index score, Control

variables)

281

+ + + + + +

+ + + + + +

Year it + it … (Models 2-5)

= + + + + + +

+ + Year it + … (Models 6-7)

Where: OPERF represents the respective dependent variable performance measure. For

Models 2-5, the dependent variables modelled are financial performance (ROA),

employee efficiency (EEF), solvency efficiency (SEF) and deposit concentration (DP)

respectively. For Models 6 and 7, MPERF represents bank market performance; the

dependent variables modelled are Tobin’s q (TOBQ) and book to market (BTM).

Coefficient in all models represents the coefficient estimate for the lagged Risk

Disclosure Index for testing the hypothesised relationship. The coefficients

within Models 2-5 and the coefficients within Models 6-7 represent year effects

to control for macroeconomic influences for each year of the analysis period 2006-2012.

is the stochastic Error term in Models 2-7. The variables and the measurement of the

variables are presented in Table 11.1.

282


Dependent ROA Return on asset (ROA) is calculated as net profit

after tax divided by total assets.

EEF Profit per employee (EEF) is measured as log of

(operating income/ no. of employee)

SEF Solvency efficiency (SEF) is capital divided by

total asset

DP Deposit (DP) is measured as bank deposits

divided total deposits of all banks

TOBQ Total assets – book value of equity + market value

of equity

BTM Book value of assets divided by market value of

assets

Independent variables Lag_RDI Prior year Risk Disclosure Index score

Control Variables LnBS Log of number of directors on the board

LnTA Natural logarithm of total assets

BI Proportion of independent directors on the board

DE Total debt divided by total equity

GDPGR GDP growth (official annual real GDP growth

Figures in per cent)

CPI Official annual Consumer Price Index in per cent

Lag_ROA Prior year return on assets

Lag_EEF Prior year profit per employee

Lag_SEF Prior year capital adequacy ratio

Lag_DP Prior year bank deposits divided total deposits of

all banks

The remainder of the Chapter is organised as follows. First descriptive statistics and

correlations for dependent, independent and control variables appear in section 11.2.

Section 11.3 presents the results of multivariate analysis in relation to examining the

association between risk disclosure and bank performance. Various performance

measures using High and Low disclosure groups are discussed in supplemental analysis

in section 11.4. Discussion of the results is presented in section 11.5 and a Chapter

summary is given in section 11.6. Figure 11.1 provides an overview of this Chapter.

50Table 11.1: Variable definitions

283

Figure 11.1 Roadmap of Chapter

11.2 Descriptives, t-tests and correlations

This section reports descriptive statistics, t-tests and correlations for the key variables.

Table 11.2 presents the descriptive statistics by complete sample and sub-sample

(conventional [Non-Islamic] and non-conventional [Islamic]). The table also includes t-

tests to compare the mean differences between the Non-Islamic and Islamic sub-

samples.

Introduction

(11.1)

Descriptives, t-tests

and correlation

(11.2)

Regression

analysis (11.3)

Supplemental

analysis (11.4)

Discussion (11.5) Chapter conclusion

(11.6)

284

Full sample (N=210) Conventional (Non-Islamic) banks (N=161 or

77%)

Non-Conventional (Islamic) banks (N=49 or 23%) t-test Sig.(2 tailed)

Mean Median Std.Dev. Mean Median Min. Max. Std.Dev. Mean Median Min. Max. Std.Dev.

ROA 1.17 1.3 1.8 1.51 1.42 -1.35 5.18 0.93 0.04 1.03 -10.85 2.65 3.07 5.35 .000

EEF 0.69 0.68 0.74 0.84 0.72 -0.40 2.49 0.54 0.19 0.44 -3.89 1.36 1.05 5.76 .000

DP 0.9 0.81 0.86 0.93 0.81 0.09 8.14 0.98 0.79 0.80 0.58 0.98 0.08 .95 .340

SEF 0.13 0.68 0.67 0.10 0.11 -0.09 0.15 0.03 -0.15 0.11 -4.68 0.18 0.98 3.35 .001

TOBQ 0.85 0.85 0.21 0.84 0.84 0.05 2.01 0.23 0.90 0.89 0.72 1.13 0.10 -1.72 .086

BTM 0.79 0.73 0.98 0.82 0.73 -0.39 10.39 1.10 0.71 0.75 0.01 2.83 0.37 .66 .509

RDI 0.62 0.64 0.19 0.65 0.67 0.20 0.87 0.17 0.52 0.53 0.18 0.83 0.19 4.29 .000

BS 13.86 14 4.4 13.54 14.00 6.00 23.00 4.14 14.90 14.00 5.00 23.00 5.08 -1.90 .059

TA 84.18 68 82.27 82.88 71.00 15.00 824.00 70.91 88.45 47.00 15.00 502.00 112.64 -.41 .679

BI 0.05 0.05 0.04 0.05 0.06 0.00 0.25 0.04 0.03 0.00 0.00 0.20 0.04 4.12 .000

GDPGR 6.25 6.19 0.33 6.25 6.19 5.74 6.71 0.33 6.25 6.19 5.74 6.71 0.33 - -

CPI 7.89 8.1 1.72 7.89 8.10 5.40 10.70 1.72 7.89 8.10 5.40 10.70 1.74 - -

DE 0.93 0.81 0.95 0.97 0.81 0.09 7.88 1.08 0.80 0.80 0.66 0.98 0.07 1.13 .258

Legend: This Table shows the descriptive statistics for the study variables in this Chapter for full sample (210 bank-years). ROA denotes Return on assets (calculated as net

profit after tax divided by total assets), EEF denotes employee efficiency (measured as log of operating income/number of employees), DP denotes bank deposit concentration

calculated as bank deposits divided by total deposits for all banks, SEF denotes solvency efficiency (measured as capital divided by total assets). TOBQ denotes Tobin’s q and

is calculated as total assets-book value of equity + market value of equity and BTM denotes book to market value of assets (calculated as book value of assets divided by

market value of assets). RDI denotes Risk Disclosure Index score (measured as per Chapter 5), BS denotes board size (number of directors on the board), TA denotes bank

size measured as total assets, BI denotes Board Independence (proportion of independent directors on the board). GDP denotes GDP growth (official annual real GDP growth

Figures in percentage terms), CPI denotes inflation rate (official annual consumer price index in percentage terms) and DE denotes leverage, measured as debt to equity ratio.

51Table 11.2: Descriptive and t- statistics by complete sample (bank years N= 210) and sub-sample (Islamic N=49, Non-Islamic N=161)

285

Table 11.2 reports descriptive statistics for the measurement of bank performance

included in this study. The Table includes descriptive statistics for full sample (210

bank-year) and sub-sample (Islamic and Non-Islamic). The mean return on assets

(ROA) for full sample is 1.17 (Non-Islamic mean is 1.51 and Islamic mean is 0.04). A t-

test shows that the mean difference between the Islamic and Non-Islamic banks is

highly significant, indicating that Non-Islamic banks have higher return on assets. The

average employee efficiency (EEF) of 0.84 is higher for Non-Islamic banks compared

to the mean of 0.19 for the Islamic banks with a t- test showing a significant difference

(at p <0.001 level) between these two groups. The solvency efficiency, SEF, (mean

0.10) and board independence, TOBQ (mean 0.82), Risk Disclosure Index, RDI (mean

0.65), BI (mean 0.05) are higher in Non-Islamic banks compare to Islamic banks and

significantly different (at p <0.001 level).

Table 11.2 further reveals that Non-Islamic banks have higher deposit concentration,

DP, (mean 0.93), higher book to market value of asset, BTM, (mean 0.82), higher total

asset, TA, (mean 82.88), debt to equity ratio, DE (mean 0.97) compared to Islamic

banks, however, the mean differences are not statistically significant. The average board

size, BS, (mean 14.90) is higher in Islamic banks compared to Non-Islamic banks and

the mean difference is significant (at p <0.01 level).

Table 11.3 reports the Pearson correlation coefficients and their significance levels for

the variables. Table 11.3 reports that the highest coefficient correlation is 0.565 between

employee efficiency (EEF) and financial performance (ROA). Therefore, Table 11.3

provides no indication that an unacceptably high level of multicollinearity concerns

exist amongst the independent variables.

286

ROA EEF SEF DP TOBQ BTM LnBS BI LnTA Lag_RDI CPI GDPGR DE

ROA 1.000

EEF 0.565**

1.000

SEF 0.340**

0.322**

1.000

DP 0.092 0.023 0.001 1.000

TOBQ 0.022 0.121 -0.048 0.048 1.000

BTM -0.014 -0.033 -0.037 -0.031 0.014 1.000

LnBS 0.500**

0.439**

0.313**

0.100 0.150* -.224

** 1.000

BI 0.111 0.116 0.118 0.051 0.081 0.092 -0.078 1.000

LnTA 0.341**

0.393**

0.151**

-.267**

-0.080 0.026 0.267**

0.152* 1.000

Lag_RDI 0.206**

0.357**

0.248**

0.096 0.150**

0.012 0.157* 0.335

** 0.540

** 1.000

CPI -0.081 -0.040 0.053 0.002 0.037 -0.036 0.040 0.194**

0.232**

0.204**

1.000

GDPGR -0.082 -0.085 -0.046 -0.022 0.028 0.027 -0.049 0.082 0.015 -0.019 0.670**

1.000

DE 0.035 0.171 0.553 0.325 0.256 .021 0.151 0.161 0.154 0.163 0.215 0.021 1.000

Legend: This Table shows the correlation coefficient of study variables used in this Chapter. ROA denotes Return on assets (calculated as net profit

after tax divided by total assets), EEF denotes employee efficiency (measured as log of operating income/number of employees), DP denotes bank

deposit concentration calculated as bank deposits divided by total deposits for all banks, SEF denotes solvency efficiency (measured as capital divided

by total assets). TOBQ is calculated as total assets-book value of equity + market value of equity and BTM denotes book to market value of assets

(calculated as book value of assets divided by market value of assets). Lag_RDI denotes prior year Risk Disclosure Index score (measured as per

Chapter five), BS denotes board size measured as log number of directors on the board, LnTA denotes bank size measured as log of total assets, BI

denotes Board Independence measured as proportion of independent directors on the board). GDP denotes GDP growth (official annual real GDP

growth Figures in percentage terms), CPI denotes inflation rate (official annual consumer price index in percentage terms) and DE denotes leverage,

measured as debt to equity ratio. ***, **, and * denote the level of significance at 1%, 5% and 10%, respectively.

52Table 11.3: Pearson’s Correlations Pooled Data (2006-2012) for Models 2-7 (N=210)

287

Table 11.3 shows the Pearson’s correlations between performance variables including

financial performance (ROA), employee efficiency (EEF), solvency efficiency (SEF),

deposit concentration (DP), Tobin’s q (TOBQ), book to market ratio (BTM) and

Lag_Risk Disclosure Index (Lag_RDI). Of all six-performance variables, ROA, EEF,

and SEF are moderately and positively significantly correlated with the lagged Risk

Disclosure Index (0.206, 0.357, and 0.238 respectively). TOBQ is marginally

significantly correlated (0.150) with the lagged Risk Disclosure Index (Lag_RDI).

Other significant correlations include log board size (LnBS) with ROA, EEF, SEF,

TOBQ and BTM. Further, log of bank size (LnSIZE) is correlated with ROA, EEF,

SEF, DP, TOBQ and LnBS. Together, these significant correlations point to an

association between the Risk Disclosure Index and bank performance on a bivariate

basis.

11.3 Regression analysis

Table 11.4 presents the results of regressing the lagged Risk Disclosure Index

(Lag_RDI) and the control variables on return on assets (ROA: Model 2), employee

efficiency (EEF: Model 3), solvency efficiency (SEF: Model 4) and deposit

concentration (DP: Model 5). The model specification statistics point towards the

models being well specified. The F-statistics for all models are significant (at p<0.001

level) and indicate that all models explain a high proportion of the variation in the

dependent variables except for book to market (Model 7). The models explain 55 per

cent, 68 per cent, 65 per cent, 52 per cent, 43 per cent and 23 per cent of the variation in

the respective dependent variables (return on assets, employee efficiency, operating

efficiency, deposit concentration, Tobin’s q and book to market).

The independent hypothesis variable for all models is the lagged Risk Disclosure Index,

Lag_RDI in order to support arguments about causal relationships in relation to the

various measures of bank performance. Results indicate that the coefficient of Lag_RDI

in Model 3 is highly significant (at p<0.001 level) with a standardised coefficient of

1.271, indicating that including Lag_RDI in the model makes a highly significant

difference in explaining employee efficiency (EEF). Within Model 3, the variables

board size (LnBS), bank size (SIZE), board independence (BI), consumer price index

288

(CPI), and prior year performance proxies (lag_EEF, lag_SEF, Lag_DP) also have

significant relationships with employee efficiency (EEF).

Table 11.4 also reveals that Lag_RDI is moderately significant (at p<0.05 level) in

explaining financial performance (ROA). In this model, coefficients for LnBS, LnTA,

BI, lag_ROA, lag_SEF are highly positively significant predictors in explaining

financial performance.

289

Variables ROA

(Model 2)

EEF

(Model 3)

SEF

(Model 4)

DP

(Model 5)

TOBQ

(Model 6)

BTM

(Model 7)

Constant

-27.832

(-2.901)***

-8.824

(-2.642)**

-2.512

(.052)

14.715

(2.130)**

2.815

(2.861)***

-2.740

(-0.927)

Lag_RDI

1.734

(2.090)**

1.271

(3.651)***

0.440

(1.698)*

0.783

(1.141)

-0.056

(-1.687)*

0.015

(0.085)

LnBS

2.458

(4.031)***

0.861

(3.885)***

0.125

(1.984)**

0.439

(2.085)**

0.083

(2.064)**

-0.426

(1.965)**

LnTA

0.909

(2.684)***

0.282

(2.255)**

0.154

(2.512)**

-0.619

(-2.094)**

-0.085

(-1.937)*

0.177

(-1.685)*

BI

7.621

(2.004)**

2.241

(1.684)*

1.116

(1.552)

0.482

(0.672)

0.077

(0.282)

3.170

(1.059)

GDPGR

0.210

(0.115)

0.213

(1.223)

0.141

(1.224)

0.313

(1.553)

0.572

(0.572)

0.522

(0.572)

CPI

-0.258

(-3.716)

-0.084

(-2.541)**

-.013

(-1.336)

-0.027

(-0.360)

0.005

(1.461)

0.015

(-0.568)

DE

0.222

(1.259)

-0.043

(-0.492)

0.018

(1.524)

0.436

(2.503)**

-0.021

(-3.585)***

0.018

(0.591)

Lag_ROA

0.805

(3.459)***

0.008

(0.416 )

0.021

(1.986 )**

0.080

(1.580 )*

Lag_EEF

0.013

(0.410 )

0.779

(7.505 ***)

-0.008

(-0.549 )

0.038

(0.538)

53Table 11.4: Regression model (Models 2-7) with a sample of 210 bank years 2006-2012

290

Lag_SEF

0.332

(1.568)*

0.143

(1.935)**

0.237

(2.538)**

-.025

(-0.537)

Lag_DP

0.010

(0.373)

0.033

(2.035)**

-.191

(-0.121)

0.227

(1.301)

Year Dummies

Yes Yes Yes Yes Yes Yes

Adj.R-squared

0.55 0.68 0.65 0.52 0.43 0.23

F-Stat.

13.90*** 25.08*** 25.08*** 10.23*** 12.23*** 10.23***


0.132 0.153 0.154 0.145 0.126 0.143

No. of Observations 210 210 210 210 210 210

Highest VIF

2.09

2.16

1.15

2.02

1.98

1.65

Legend: The Table shows standardized coefficients, t-statistics in brackets and model specification statistics from pooled OLS regression models

regressing lagged Risk Disclosure Index (RDI) on banks’ operating performances such as financial (ROA), employee efficiency (EEF), solvency

efficiency (SEF), deposit concentration (DP) and bank market performances such as Tobin’s q (TOBQ) and book to market (BTM). Where, the

dependent variable is OPERF proxied as ROA, EEF, SEF and DP (Models 2-5). For Models 6 and 7, dependent variable is MPERF, proxied as TOBQ

and book to market (BTM). The independent variable for Models 2-7 is Lag_RDI. ROA denotes Return on assets (calculated as net profit after tax

divided by total assets), EEF denotes employee efficiency (measured as log of operating income/number of employees), DP denotes bank deposit

concentration calculated as bank deposits divided by total deposits for all banks, SEF denotes solvency efficiency (measured as capital divided by total

assets). TOBQ is calculated as total assets-book value of equity + market value of equity and BTM denotes book to market value of assets (calculated as

book value of assets divided by market value of assets). RDI denotes Risk Disclosure Index score (measured as per Chapter five), BS denotes board size

(log number of directors on the board), LnTA denotes bank size measured as log of total assets, BI denotes Board Independence (proportion of

independent directors on the board). GDP denotes GDP growth (official annual real GDP growth Figures in percentage terms), CPI denotes inflation

rate (official annual consumer price index in percentage terms) and DE denotes leverage, measured as debt to equity ratio. ***, **, and * denote the

level of significance at 1%, 5% and 10%, respectively.

291

Results in Table 11.4 also indicate that solvency efficiency, proxied by SEF, is

marginally significantly (at p<0.10 level) associated with Lag_RDI. Within Model 4,

the control variables LnBS, LnTA, Lag_ROA, Lag_SEF are significant (at p<0.05

level), respectively.

Furthermore, Pearson’s correlation coefficients (Table 11.3) show bank market

performance, proxied by TOBQ, is positively significant with Lag_RDI (at p<0.05

level). However, TOBQ is found to have a marginally negative significant relationship

with Lag_RDI, possibly indicating a market penalty for above average disclosure.

TOBQ also has a significant negative relationship with bank size (LnTA) (at p<0.10

level) and leverage (DE) (at P<0.01 level) and a positive relation with board size

(LnBS) (at p<0.05 level).

However, the other market performance metric, book to market (BTM) shows no

significant relationship with Lag_RDI but has a negative relationship with LnTA( at

p<0.10 level) and a positive relationship with LnBS (at p<0.05 level).

11.4 Supplemental analysis

This section provides supplemental analysis of Models 2-5 (financial performance,

employee efficiency, solvency efficiency, deposit concentration) by examining (1)

whether the association between the Risk Disclosure Index and various performance

measures differs across High and Low Risk Disclosure groups; (2) whether the relation

between the Risk Disclosure Index and various performance measures differs across

Non-Islamic and Islamic banks; and 3) the specific types of Risk Disclosure that have

an association with the measures of bank performances.

11.4.1 Bank performance in risk disclosure groups (High and Low)

Table 11.5 shows the descriptive statistics for the study broken down by Risk

Disclosure Index items into High Risk Disclosers and Low Risk Disclosers. The High

Risk Disclosure group consists of banks for which the Risk Disclosure Index score

292

exceeds the median score, while the Low Risk Disclosure group consists of banks with

scores that are lower than the median. Additionally, Table 11.5 shows t-test results for

the High Risk Disclosure group compared with Low Risk Disclosure group.

Table 11.5 reveals that the High Risk Disclosure group has an industry-adjusted mean

(median) return on assets (ROA) of 1.43 per cent (1.84 per cent) compared to a mean

(median) of 0.90 per cent (1.20 per cent) for the Low Risk Disclosure group. A t-test

shows the mean difference in Risk Disclosure Index between the High Risk Disclosure

group and Low Risk Disclosure group is highly significant, indicating that higher

disclosers have higher financial performance. Further, the industry-adjusted mean

(median) employee efficiency (EEF) of 0.90 (0.79) is higher for the High Risk

Disclosure group compared to the mean (median) of 0.47 (0.53) for the Low Risk

Disclosure group. Additionally, there is a significant difference (at p <0.001 level)

between these two groups. High Risk Disclosers enjoy higher deposit concentration,

DP, (mean 1.01) and higher capital adequacy, SEF, (mean 0.10) compared to 0.78 and -

0.01 for the Low Risk Disclosure group, respectively. TOBQ and book-to market

(BTM), are also higher for the High Risk Disclosure group in comparison to the Low

Risk Disclosure Group and significantly different (at p <0.001 level).

293

Legend: This Table shows the descriptive statistics for the study variables in this Chapter for full sample (210 bank-years) and classified by disclosure group (Lo: Low

Disclosure group, HI: High Disclosure group). These groups are split at the median. ROA denotes Return on assets (calculated as net profit after tax divided by total

assets), EEF denotes employee efficiency (measured as log of operating income/number of employees), DP denotes bank deposit concentration calculated as bank

deposits divided by total deposits for all banks, SEF denotes solvency efficiency (measured as capital divided by total assets). TOBQ denotes Tobin’s q and is

calculated as total assets-book value of equity + market value of equity and BTM denotes book to market value of assets (calculated as book value of assets divided by

market value of assets). RDI denotes Risk Disclosure Index score (measured as per Chapter 5), BS denotes board size (number of directors on the board), LnTA

denotes bank size measured as total assets, BI denotes Board Independence (proportion of independent directors on the board) and DE denotes leverage, measured as

debt to equity ratio.

54Table 11.5: Descriptive Statistics and t-tests for variables by Risk Disclosure groups (High and Low) (210 bank-years)

Variables Discl.

Group

Mean Median Std.

Deviation

Minimum Maximum t-test Sig.

(2 tailed)

ROA

HI 1.43 1.52 1.68 -9.97 5.18

3.04

0.000 LO 0.90 1.20 1.88 -10.85 3.91

EEF HI 0.90 0.79 0.69 -2.62 2.49

4.34

0.000 LO 0.47 0.53 0.74 -3.89 1.84

DP HI 1.01 0.81 1.20 0.63 8.14

1.94

0.050 LO 0.78 0.81 0.11 0.09 0.98

SEF HI 0.40 0.96 1.21 0.52 7.16

1.58

0.114 LO -0.14 0.41 0.14 -0.11 0.53

TOBQ HI 0.85 0.86 0.12 0.07 1.13

2.96

0.000 LO 0.86 0.84 0.27 0.05 2.01

BTM HI 0.79 0.73 0.97 -0.39 10.39

2.90

0.040 LO 0.80 0.72 0.99 -0.03 10.39

RDI HI 0.77 0.78 0.07 0.64 0.87

8.65

0.000 LO 0.47 0.49 0.13 0.18 0.63

BS HI 14.43 14.00 4.72 5.00 23.00

2.17

0.020 LO 13.29 14.00 4.00 5.00 23.00

LnTA HI 103.90 91 72.57 15 502

3.58

0.000 LO 64.46 48 86.89 16 824

BI HI 0.06 0.06 0.04 0.00 0.25

3.64

0.000 LO 0.04 0.03 0.04 0.00 0.17

DE HI 1.06 0.81 1.33 0.49 7.88

1.14

0.250 LO 0.81 0.81 0.10 0.09 0.98

294

Table 11.5 also reveals that the High Risk Disclosure group, on average has larger

boards, more independent boards and higher debt to equity ratios. Mean bank size

(LnTA) points toward the High Risk Disclosure group being on average of higher size

compared to the Low Risk Disclosure group. The mean difference is highly significant

for bank size (LnTA) and board independence (BI). Taken together, the t-tests in this

study suggest that High Risk Discloser banks are larger in size, have an independent

board, are extensively leveraged, have higher solvency and return on asset ratios, are

better governed with high employee efficiency and generate higher bank valuation.

Table 11.6 shows the results of regression analysis for the models with various

measures of performance as the dependent variables and the lagged Risk Disclosure

Index for each of the High and Low Risk Disclosure groups as the Hypothesis variables.

In general, the Low Risk Disclosure group has much lower variation in performances

compared to the High Risk Disclosure group. Lag_RDI is significantly (at p<.001 level)

positively related to ROA for the High Risk Disclosure group, indicating that for high

risk disclosers, lagged disclosure is strongly associated with financial performance.

Table 11.6 further reveals that the adjusted R2 for the deposit concentration (DP) model

is 0.57. This indicates that High Risk Disclosers are associated with higher deposit

concentration in the market. This possibly encourages bank management to provide a

consistent impression in the market with a self-projected image of a transparent,

straightforward bank. Additionally, the adjusted R2 for all Models is high and the F-

statistics for all four Models are significant at the 1 per cent level and explain a high

proportion of variation in the dependent variable. Further, the significant results for

variables Year 2007 and Year 2008 indicate that the period of the GFC had a significantly

negative impact on financial performance (ROA), employee efficiency (EEF) and

deposit concentration (DP) for the High Risk Disclosure group.

295

55Table 11.6: Regression results for High and Low Risk Disclosure groups with a sample of 210 bank years 2006-2012

Variables ROA EEF OEF DP

HI LO HI LO HI LO HI LO

Constant -12.937** -21.141 -4.328 -6.183 -0.221 5.7719* 20.7453** 0.245

(-2.27) (-1.078) (-1.563) (-0.790) (-0.328) (-1.844) (-2.152) (-0.378)

Lag_RDI 1.755*** 0.330 -0.7141* 0.249 -0.014 0.094 0.695 0.1713**

-2.720 -0.498 (-1.807) (-0.876) (-0.110) (-0.607) (-0.576) (-2.131)

LnBS 0.220 0.868 0.052 0.254 0.020 -0.074 0.328 -0.020

(-1.171) (-1.191) (-0.474) (-0.896) (-0.123) (-0.934) (-1.486) (-1.036)

LnTA 0.039 0.301 0.051 0.051 0.019 -0.145 -1.1982** -0.027

(-0.345) (-0.891) (-0.834) (-0.389) (-1.122) (-1.632) (-2.449) (-1.476)

BI 2.951 2.928 0.389 0.706 -0.101* -0.718 -0.296 -0.240

(-1.200) (-0.900) (-0.413) (-0.548) (-1.122) (-1.269) (-0.244) (-1.191)

GDPGR 2.7824*** 2.540 0.8347* 0.994 -0.117 -0.246 1.8142* 0.086

(-3.003) (-1.264) (-1.737) (-1.154) (-0.511) (-1.100) (-1.756) (-0.834)

CPI -0.6052*** -0.582 -0.1969** -0.221 0.017 0.053 -0.335 -0.014

(-3.427) (-1.399) (-2.175) (-1.225) (-0.211) (-1.240) (-1.615) (-0.664)

DE 0.0529* 0.670 -0.024 -0.023 0.021 -0.989 0.3380** 0.7545***

(-1.726) (-0.442) (-1.520) (-0.037) (-0.211) (-1.428) (-2.121) (-4.920)

Lag_ROA 0.5475*** 0.6485*** -0.038 -0.022 0.0150* 0.036 0.1975** 0.007

(-5.067) (-4.380) (-0.362) (-0.304) (-1.665) (-1.553) (-2.579) (-0.861)

Lag_EEF 0.034 0.278 0.7767*** 0.8052*** -0.010 -0.008 0.100 -0.011

(-0.200) (-1.000) (-4.786) (-5.637) (-1.022) (-0.196) (-0.661) (-0.540)

Lag_SEF 7.8386*** 0.235 1.620 0.123 0.9701*** 0.6546*** -1.446 0.010

(-2.769) (-1.134) (-1.142) (-1.411) (-5.109) (-2.786) (-1.318) (-0.870)

ROA EEF OEF DP

296

Legend: The Table shows standardised coefficients, t statistics in the parentheses and model specification statistics from pooled OLS

regression models regressing bank’s financial performance (ROA), employee efficiency (EEF), solvency efficiency (SEF), and deposit

concentration (DP) on lagged High and Low Risk Disclosure Index groups. The High Risk Disclosure group consists of banks where the

Risk Disclosure Index (RDI) score exceeds the median score 0.64 (calculated in Table 8.1, Chapter 8: Descriptive statistics), while the Low

Risk Disclosure group consists of banks with RDI scores that are lower than the median.

ROA denotes return on assets (calculated as net profit after tax divided by total assets), EEF denotes employee efficiency (measured as log

of operating income/number of employees), DP denotes bank deposit concentration calculated as bank deposits divided by total deposits

for all banks, SEF denotes solvency efficiency (measured as capital divided by total assets). TOBQ is calculated as total assets-book value

of equity + market value of equity and BTM denotes book to market value of assets (calculated as book value of assets divided by market

value of assets). RDI denotes Risk Disclosure Index score (measured as per Chapter 8), BS denotes board size (log number of directors on

the board), LnTA denotes bank size measured as log of total assets, BI denotes Board Independence (proportion of independent directors

on the board). GDP denotes GDP growth (official annual real GDP growth Figures in percentage terms), CPI denotes inflation rate (official

annual consumer price index in percentage terms) and DE denotes leverage, measured as debt to equity ratio. Year 2007 and Year 2008 are

year dummies for year 2007 and year 2008.

***, **, and * denote the level of significance at 1%, 5% and 10%, respectively.

Lag_DP 0.028 -0.122 0.0359* -0.011 -0.001 -0.077 0.184 0.229

(-1.162) (-0.172) (-1.958) (-0.035) (-1.105) (-0.585) (-1.469) (-1.313)

Year 2007 -1.8756*** -1.661 -0.6777* -0.718 0.028 0.027 -1.9267** -0.055

(-2.821) (-1.393) (-1.951) (-1.294) (-0.739) (-0.170) (-2.014) (-0.702)

Year 2008 -0.329 0.101 -0.139 -0.078 0.005 0.023 -0.5998** -0.033

(-1.487) (-0.389) (-1.416) (-0.718) (-0.631) (-0.475) (-2.015) (-1.642)

Observations 103 77 103 77 103 77 103 77

Adj. R-

squared

0.797 0.777 0.691 0.730 0.914 0.772 0.573 0.624

F-Stat. 10.21*** 11.64*** 28.86*** 15.54*** 24.48*** 4.54*** 5.95*** 22.54***

Highest VIF 2.130 1.230 1.990 1.960 2.130 1.240 1.780 1.450

297

11.4.2 Bank performance and risk disclosure in Non-Islamic and Islamic

banks

This section reports the regression results estimating the factors associated with bank

performance for 30 banks (23 Non-Islamic and 7 Islamic) over a period of seven-years

from 2006-2012. Table 11.7 presents the results of regressing the lagged Risk disclosure

Index (Lag_RDI) and the control variables on return on assets (ROA:Model 2),

employee efficiency (EEF: Model 3), solvency efficiency (SEF: Model 4), deposit

concentration (DP: Model 5), Tobin’s q (Model 6) and book-to market (BTM: Model

7).

The adjusted coefficient of determination (adjusted R2) indicates that the models explain

77 per cent, 74 per cent, 76 per cent, 31 per cent, 44 per cent, and 43 per cent of the

variation of the respective dependent variables (ROA, EEF, SEF, DP, Tobin’s q and

BTM) and the models are highly significant (at p<0.001 level). Table 11.7 reveals that

Lag_RDI, is significant in explaining financial performance (ROA), employee

efficiency (EEF), solvency efficiency (SEF) (at p<0.1 level) and deposit concentration

(DP) at p<0.05 level. The indicator variable Non-Islamic bank is moderately significant

(at p<0.05 level) in the models with ROA, EEF and Tobin’s q as the dependent

variables. Further relationships exist with control variables board size (LnBS), bank size

(LnTA), (at p< 0.1 level) and lag ROA (at p<0.1) Model 2. Additionally, in Model 3,

bank size (LnTA), lag solvency efficiency (Lag_SEF) are significant (at p< 0.01 level).

GDP growth (GDPGR), consumer price Index (CPI) (at p< 0.05 level), and lag

efficiency (Lag_EEF) are also significant (at p< 0.001 level) in this Model.

298

VARIABLES ROA

(Model 2)

EEF

(Model 3)

SEF

(Model 4)

DP

(Model 5)

TOBQ

(Model 6)

BTM

(Model 7)

Constant 0.486 0.593 0.341 19.344** 2.602** -2.932

(0.129)

(0.398) (1.041) (2.189) (2.443) (-1.349)

Lag_RDI 0.596* 0.119* 0.011* 1.412** 0.001 0.225

(1.696)

(1.804) (1.769) (1.978) (0.010) (0.770)

LnBS 0.435* 0.100 0.018* 0.263* 0.060* -0.397

(1.685)

(0.792) (1.678) (1.755) (1.682) (-1.285)

LnTA 0.058 0.043* 0.003* 0.751** 0.074* 0.129*

(1.689)*

(1.697) (0.594) (2.211) (1.765) (1.843)

BI 1.029 -0.310 0.248* 0.082 0.193 3.428

(0.607)

(-0.465) (1.835) (0.095) (0.525) (1.299)

GDPGR -0.269 -0.214** -0.020 0.208 -0.015 0.184

(-1.212)

(-2.169) (-0.893) (0.980) (-0.362) (1.012)

CPI -0.087 -0.033 -0.006 -0.020 0.009 0.029

(-1.617)

(-1.544) (-1.462) (-0.578) (0.110) (1.053)

DE -0.396 -0.429** 0.130** 0.345 0.014 0.238

(-0.671)

(-2.119) (2.221) (1.325) (0.167) (1.117)

Lag_ROA 0.852*** 0.032 0.011 0.187* -0.013 0.029

(7.171)

(0.582) (1.315) (1.778) (-0.818) (0.465)

Lag_EEF -0.127 0.733*** 0.005 -0.273 0.089*** -0.021

56Table 11.7 :Regression results for High and Low Risk Disclosure groups with a sample of 210 bank years 2006-2012

299

(-0.771)

(7.195) (0.740) (-1.186) (2.977) (-0.226)

Lag_SEF 0.369 0.153* 0.632** -0.028 0.046* -0.196

(1.593)

(1.796) (2.515) (-0.543) (1.731) (-1.187)

Lag_DP -0.002 0.011 0.009 0.374 -0.010 0.006

(-0.080)

(0.605) (0.389) (1.361) (-0.986) (0.306)

Non-Islamic 0.297** 0.121** 0.009 -0.059 0.170** 0.050

(2.050)

(2.085) (0.935) (-0.555) (1.960) (0.763)

Year Dummies Yes

Yes Yes Yes Yes Yes

Adj. R-squared 0.77

0.74 0.76 0.31 0.44 0.43

F-Stat 22***

31*** 32*** 10*** 11*** 12***

White Stat. (p-value) 0.124

0.221 0.131 0.152 0.127 0.156

Number of Observations 210

210 210 210 210 210

Highest VIF 1.96 2.11 2.14 1.36 1.52 2.15

Legend: The Table shows standardized coefficients, t-statistics in brackets and model specification statistics from pooled OLS regression models regressing lagged Risk

Disclosure Index (RDI) on banks’ operating performances such as financial (ROA), employee efficiency (EEF), solvency efficiency (SEF), deposit concentration (DP) and

bank market performances such as Tobin’s q (TOBQ) and book to market (BTM). Where, the dependent variable is OPERF proxied as ROA, EEF, SEF and DP (Models 2-

5). For Models 6 and 7, dependent variable is MPERF, proxied as TOBQ and book to market (BTM). The independent variable for Models 2-7 is Lag_RDI. ROA denotes

Return on assets (calculated as net profit after tax divided by total assets), EEF denotes employee efficiency (measured as log of operating income/number of employees), DP

denotes bank deposit concentration calculated as bank deposits divided by total deposits for all banks, SEF denotes solvency efficiency (measured as capital divided by total

assets). TOBQ is calculated as total assets-book value of equity + market value of equity and BTM denotes book to market value of assets (calculated as book value of assets

divided by market value of assets). RDI denotes Risk Disclosure Index score (measured as per Chapter 8), BS denotes board size (log number of directors on the board),

LnTA denotes bank size measured as log of total assets, BI denotes Board Independence (proportion of independent directors on the board). GDP denotes GDP growth

(official annual real GDP growth Figures in percentage terms), CPI denotes inflation rate (official annual consumer price index in percentage terms) and DE denotes leverage,

measured as debt to equity ratio. Non-Islamic is an indicator variable for Non-Islamic banks. ***, **, and * denote the level of significance at 1%, 5% and 10%, respectively.

300

Table 11.7 further reports that no significant relationship exist with the indicator

variable Non-Islamic in solvency efficiency (SEF), deposit concentration (DP) and

book-to-market (BTM). However, the control variable, board size (LnBS), is explaining

the association with SEF and Tobin’s q (at p<0.01 level), bank size (LnTA) with all

Models at p<0.01 level except DP at p<0.05 level. The debt to equity ratio is

significantly (at 0.05 level) associated with EEF and SEF.

11.4.3 Bank performance and Risk Types

As discussed in Chapter 7, the composite Risk Disclosure Index includes five types of

Risk Disclosure, comprised of Market, Credit, Liquidity, Operational and Equities.

Tables 11.8 to 11.12 show the results of regressing the lagged Market Risk Disclosure

Index (Lag_MRDI), lagged Credit Risk Disclosure Index (Lag_CRDI), lagged Liquidity

Risk Disclosure Index (Lag_LRDI), lagged Operational Risk Disclosure Index

(Lag_ORDI) and lagged Equities Risk Disclosure Index (Lag_ERDI) on bank

performance. Performance measures are the dependent variables following Models 2-7

as explained in section 11.3. The definitions for control variables are the same as for

Models 2-7.

The analysis examines the variation in the performance proxies for types of Risk

Disclosure Index for the full sample (210 bank years). Tables 11.8 to 11.12 suggest

lagged Market Risk Disclosure Index (Lag_MRDI) and lagged Equities Risk Disclosure

Index (Lag_ERDI) are highly (at p<.001 level) significantly related to ROA. Further,

significant relationships exist with control variables board size (LnBS), bank size (Size),

board independence (BI), consumer price index (CPI) and lag ROA. The F-statistic is

significant and the adjusted R2

is reasonable for all models presented in Table 11.5 to

11.9.

Tables 11.8 to 11.12 also reveal that employee efficiency (EEF) is significantly (at

p<.01) positively related to the lagged Market Risk Disclosure Index (Lag_MRDI) and

lagged Equities Risk Disclosure Index (Lag_ERDI). Most control variables are

significantly related to EEF. The F-statistic is significant at the p<.01 level however, the

301

adjusted R2s are 36 per cent, 29 per cent, 14 per cent, and 42 per cent for the lagged

Credit Risk Disclosure Index (Lag_CRDI) in models 2-5 respectively. Additionally, the

adjusted R2s for lagged Liquidity Risk Disclosure Index (Lag_LRDI) are 0.40, 0.33,

0.28, and 0.45. Of the five types of Risk Disclosure included in the Index, only

Lag_MRDI is marginally significantly (at p<0.1 level) in its association with solvency

efficiency (SEF).

302

VARIABLES ROA

(Model 2)

EEF

(Model 3)

SEF

(Model 4)

DP

(Model 5)

Constant -29.275*** -10.096*** -3.477** 13.735**

(-3.081) (-2.911) (-2.121) (2.191)

Lag_MRDI 1.817*** 0.911*** 0.339* -0.179

(3.132) (3.550) (1.691) (-1.063)

LnBS 2.451*** 0.860*** 0.357** 0.442**

(4.180) (4.001) (2.001) (2.034)

LnTA 1.034*** 0.374*** 0.108** -0.562**

(2.918) (2.814) (2.075) (-2.197)

BI 7.970** 2.681** 1.122 0.918

(2.140) (2.011) (1.430) (1.281)

GDPGR 0.399 0.117* 0.628** -0.004

(1.112) (1.224) (2.495) (-0.127)

CPI -0.160** -0.026 0.005 -0.005

(-2.125) (-0.774) (0.637) (-0.144)

DE 0.280** -0.009 0.019** 0.447**

(2.114) (-0.234) (2.437) (2.125)

Lag_ROA 0.794*** 0.006 0.022* 0.066

(8.881) (0.122) (1.852) (1.424)

Lag_EEF 0.017 0.774*** -0.009 0.098

(0.137) (7.417) (-0.790) (0.631)

Lag_SEF 0.299 0.127* 0.638** -0.004

(1.511) (1.721) (2.590) (-0.120)

Lag_DP 0.001 0.029* -0.002 0.235

(0.050) (1.880) (-0.061) (1.371)

57Table 11.8 : Regression results (Independent hypothesis variable=Lag_Market Risk Disclosure Index)


303

Year Dummies Yes Yes Yes Yes

Adj. R-squared

0.410 0.563 0.471 0.475

F-Stat.

11.69*** 23.18*** 15.23*** 10.16***

Highest VIF 1.96 2.10 1.10 1.85

Legend: The Table shows standardised coefficients, t statistics in brackets and model specification statistics from main pooled OLS regression

models regressing lagged Market Risk Disclosure Index (MRDI) on bank’s financial (ROA), employee efficiency (EEF), solvency efficiency

(SEF), and deposit concentration (DP). The regression Model in Table 11.5 is as follows.

+ + + + + + + + + +

+ + + it

Where, the dependent variable is OPERF proxied as ROA, EEF, SEF or DP and the independent variable is Lag_MRDI. ROA denotes Return on

assets (calculated as net profit after tax divided by total assets), EEF denotes employee efficiency (measured as log of operating income/number

of employees), DP denotes bank deposit concentration calculated as bank deposits divided by total deposits for all banks, SEF denotes solvency

efficiency (measured as capital divided by total assets). TOBQ is calculated as total assets-book value of equity + market value of equity and

BTM denotes book to market value of assets (calculated as book value of assets divided by market value of assets). Lag_MRDI denotes prior

year Market Risk Disclosure Index score (measured in Chapter 5), BS denotes board size (number of directors on the board), LnTA denotes bank

size measured as total assets, BI denotes board independence (proportion of independent directors on the board). GDP denotes GDP growth

(official annual real GDP growth Figures in percentage terms), CPI denotes inflation rate (official annual consumer price index in percentage

terms) and DE denotes leverage, measured as debt to equity ratio. Lag_ROA, Lag_EEF, Lag_OEF and Lag_DP are prior year lagged

performance. ***, **, and * denote the level of significance at 1%, 5% and 10%, respectively.

304

VARIABLES ROA

(Model 2)

EEF

(Model 3)

SEF

(Model 4)

DP

(Model 5)

Constant -30.130*** -10.449*** -3.542** 13.679**

(-2.960) (-2.761) (-2.101) (2.184)

Lag_CRDI -0.172 -0.271 -0.263 -0.084

(-0.275) (-0.975) (-1.295) (-0.364)

LnBS 2.460*** 0.855*** 0.347** 0.440**

(3.882) (3.592) (1.994) (2.044)

LnTA 1.035*** 0.376*** 0.110** -0.561**

(2.765) (2.635) (2.015) (-2.197)

BI 8.803** 3.145** 1.337 1.017

(2.177) (2.107) (1.448) (1.329)

GDPGR 0.115 0.25* 0.637** -0.01

(1.301) (1.755) (2.594) (-0.265)

CPI -0.219*** -0.051 0.004 -0.009

(-2.724) (-1.446) (0.026) (-0.274)

DE 0.242* -0.024 0.017* 0.445**

(1.767) (-0.526) (1.927) (2.106)

Lag_ROA 0.794*** 0.008 0.022* 0.066

(8.977) (0.156) (1.846) (1.466)

Lag_EEF 0.048 0.789*** -0.010 0.094

(0.367) (7.566) (-0.887) (0.607)

Lag_SEF 0.325 0.135* 0.637** -0.010

(1.604) (1.757) (2.597) (-0.268)

58Table 11.9: Regression results (Independent hypothesis variable=Lag Credit Risk Disclosure Index)


305

Lag_DP 0.008 0.031* -0.005 0.233

(0.281) (1.911) (-0.172) (1.354)


Adj. R-squared

0.367 0.293 0.140 0.424

F-Stat.

5.27*** 4.22*** 6.22*** 3.19***

Highest VIF 1.19 1.36 2.10 1.68

Legend: The Table shows standardised coefficients, t statistics in brackets and model specification statistics from main pooled OLS regression

models regressing lagged Market Risk Disclosure Index (MRDI) on bank’s financial (ROA), employee efficiency (EEF), solvency efficiency

(SEF), and deposit concentration (DP). The regression Model in Table 11.6 is as follows.

+ + + + + + + + + +

+ + + it

Where, Dependent variable is OPERF proxied as ROA, EEF, SEF and DP and independent variable is Lag_CRDI. ROA denotes Return on

assets (calculated as net profit after tax divided by total assets), EEF denotes employee efficiency (measured as log of operating income/number

of employees), DP denotes bank deposit concentration calculated as bank deposits divided by total deposits for all banks, SEF denotes solvency

efficiency (measured as capital divided by total assets). TOBQ is calculated as total assets-book value of equity + market value of equity and

BTM denotes book to market value of assets (calculated as book value of assets divided by market value of assets). Lag_CRDI denotes Credit

Risk Disclosure Index score (measured in Chapter five), BS denotes board size (number of directors on the board), LnTA denotes bank size

measured as total assets, BI denotes board independence (proportion of independent directors on the board). GDP denotes GDP growth (official

annual real GDP growth Figures in percentage terms), CPI denotes inflation rate (official annual consumer price index in percentage terms) and

DE denotes leverage, measured as debt to equity ratio. Lag_ROA, Lag_EEF, Lag_SEF and Lag_DP are prior year lagged performance.


306

VARIABLES ROA

(Model 2)

EEF

(Model 3)

SEF

(Model 4)

DP

(Model 5)

Constant -29.415*** -10.377*** -3.351** 13.416**

(-2.900) (-2.761) (-2.120) (2.221)

Lag_LRDI -0.612 -0.142 -0.232 0.177

(-1.031) (-0.522) (-1.371) (0.794)

LnBS 2.398*** 0.853*** 0.333** 0.465*

(3.834) (3.615) (1.994) (1.974)

LnTA 1.022*** 0.371*** 0.104** -0.558**

(2.744) (2.607) (2.042) (-2.201)

BI 8.880** 3.103** 1.315 0.960

(2.204) (2.081) (1.441) (1.312)

GDPGR 0.330 0.146* 0.637** -0.002

(1.642) (1.945) (2.596) (-0.076)

CPI -0.207** -0.054 -0.005 -0.016

(-2.536) (-1.496) (-0.076) (-0.404)

DE 0.247* -0.028 0.015** 0.441**

(1.814) (-0.625) (2.004) (2.075)

Lag_ROA 0.791*** 0.005 0.022* 0.068

(8.955) (0.104) (1.885) (1.485)

Lag_EEF 0.051 0.791*** -0.011 0.090

(0.394) (7.445) (-0.914) (0.585)

Lag_SEF 0.330 0.146* 0.637** -0.002

(1.644) (1.944) (2.595) (-0.075)

Lag_DP 0.011 0.034** -0.008 0.232

59Table 11.10 : Regression results (Independent hypothesis variable=Lag Solvency Risk Disclosure Index)


307

(0.404) (2.055) (-0.305) (1.355)


Adj. R-squared

0.405 0.330 0.284 0.457

F-Stat.

3.33*** 4.35*** 5.36*** 3.65

Highest VIF 1.25 1.96 2.1 1.65

Legend: The Table shows standardised coefficients, t statistics in brackets and model specification statistics from main pooled OLS regression models

regressing lagged Market Risk Disclosure Index (MRDI) on bank’s financial (ROA), employee efficiency (EEF), solvency efficiency (SEF), and deposit

concentration (DP). The regression Model in Table 11.7 is as follows.

+ + + + + + + + + +

+ + + it

Where, Dependent variable is OPERF proxied as ROA, EEF, OEF and DP and independent variable is Lag_LRDI. ROA denotes Return on assets (calculated

as net profit after tax divided by total assets), EEF denotes employee efficiency (measured as log of operating income/number of employees), DP denotes bank

deposit concentration calculated as bank deposits divided by total deposits for all banks, SEF denotes solvency efficiency (measured as capital divided by total

assets). TOBQ is calculated as total assets-book value of equity + market value of equity and BTM denotes book to market value of assets (calculated as book

value of assets divided by market value of assets). Lag_LRDI denotes Liquidity Risk Disclosure Index score (measured in Chapter five), BS denotes board

size (number of directors on the board), LnTA denotes bank size measured as total assets, BI denotes board independence (proportion of independent directors

on the board). GDP denotes GDP growth (official annual real GDP growth Figures in percentage terms), CPI denotes inflation rate (official annual consumer

price index in percentage terms) and DE denotes leverage, measured as debt to equity ratio. Lag_ROA, Lag_EEF, Lag_SEF and Lag_DP are prior year lagged

performance. ***, **, and * denote the level of significance at 1%, 5% and 10%, respectively.

308

VARIABLES ROA

(Model 2)

EEF

(Model 3)

SEF

(Model 4)

DP

(Model 5)

Constant -30.049*** -10.504*** -3.693** 13.781**

(-2.980) (-2.781) (-2.041) (2.221)

Lag_ORDI 0.280 0.104 -0.078 0.253*

(0.741) (0.702) (-0.854) (1.935)

LnBS 2.526*** 0.890*** 0.344** 0.495**

(3.830) (3.634) (2.032) (2.095)

LnTA 1.016*** 0.367** 0.114* -0.579**

(2.774) (2.602) (1.952) (-2.224)

BI 8.557** 3.000** 1.325 0.814

(2.154) (2.042) (1.404) (1.154)

GDPGR 0.338* 0.148* 0.637** 0.005

(1.674) (1.955) (2.604) (0.155)

CPI -0.229*** -0.061* -0.005 -0.016

(-2.877) (-1.735) (-0.702) (-0.452)

DE 0.234* -0.032 0.013 0.439**

(1.762) (-0.732) (1.657) (2.107)

Lag_ROA 0.791*** 0.005 0.022* 0.064

(9.027) (0.102) (1.862) (1.352)

Lag_EEF 0.048 0.791*** -0.011 0.091

(0.370) (7.360) (-0.920) (0.574)

Lag_SEF 0.338* 0.148* 0.637** 0.005

(1.674) (1.954) (2.600) (0.154)

Lag_DP 0.011 0.034** -0.007 0.234

60Table 11.11 : Regression results (Independent hypothesis variable=Lag Operational Risk Disclosure Index)


309

(0.394) (2.044) (-0.244) (1.384)

Year Dummies

Yes Yes Yes Yes

Adj. R-squared

0.369 0.291 0.130 0.429

F-Stat.

5.36*** 4.56*** 5.66** 6.21***

Highest VIF 1.56 1.25 1.26 1.63

Legend: The Table shows standardized coefficient , t stat. in the parentheses and model specification statistics from main pooled OLS regression models

regressing bank’s financial (ROA), employee efficiency (EEF), Solvency efficiency (SEF), and deposit concentration (DP) on lagged Operational Risk

Disclosure Index (LRDI). The regression Model in Table 11.8 is as follows.

+ + + + + + + + + +

+ + + it

Where, Dependent variable is OPERF proxied as ROA, EEF, SEF and DP and independent variable is Lag_ORDI. ROA denotes Return on assets (calculated




value of assets divided by market value of assets). Lag_ORDI denotes Operational Risk Disclosure Index score (measured in Chapter 5), BS denotes board

size (number of directors in the board), BS denotes board size (number of directors on the board), LnTA denotes bank size measured as total assets, BI denotes

board independence (proportion of independent directors on the board). GDP denotes GDP growth (official annual real GDP growth Figures in percentage

terms), CPI denotes inflation rate (official annual consumer price index in percentage terms) and DE denotes leverage, measured as debt to equity ratio.

Lag_ROA, Lag_EEF, Lag_SEF and Lag_DP are prior year lagged performance. ***, **, and * denote the level of significance at 1%, 5% and 10%,

respectively.

310

VARIABLES ROA

(Model 2)

EEF

(Model 3)

SEF

(Model 4)

DP

(Model 5)

Constant -28.576*** -9.940*** -3.516** 14.046**

(-2.930) (-2.694) (-2.050) (2.180)

Lag_ERDI 0.899** 0.343** 0.074 0.222

(2.424) (2.090) (1.434) (1.104)

LnBS 2.591*** 0.916*** 0.370* 0.474**

(4.024) (3.804) (1.944) (1.984)

LnTA 0.947*** 0.341** 0.101** -0.583**

(2.645) (2.442) (2.000) (-2.161)

BI 7.568* 2.620* 1.170 0.701

(1.944) (1.815) (1.385) (1.054)

GDPGR 0.046 0.790*** -0.011 0.092

(0.367) (7.245) (-0.904) (0.595)

CPI -0.254*** -0.070** -0.009 -0.019

(-3.114) (-2.004) (-1.075) (-0.465)

DE 0.205 -0.043 0.009 0.435**

(1.555) (-0.965) (1.364) (2.054)

Lag_ROA 0.786*** 0.003 0.022* 0.063

(9.025) (0.067) (1.847) (1.317)

Lag_EEF 0.046 0.790*** -0.011 0.092

(0.367) (7.248) (-0.907) (0.597)

Lag_SEF 0.332 0.146* 0.636** -0.010

(1.644) (1.973) (2.577) (-0.305)

Lag_DP 0.013 0.035** -0.006 0.231

61Table 11.12: Regression results (Independent variable=Lag Equities Risk Disclosure Index) with a sample of 210

bank years 2006-2012

311

(0.494) (2.1835) (-0.234) (1.365)


Adj. R-squared

0.408 0.559 0.571 0.475

F-Stat.

5.56*** 6.34*** 6.35*** 7.65***

Highest VIF 1.26 2.21 2.31 1.98

Legend: The Table shows standardized coefficient , t stat. in the parentheses and model specification statistics from main pooled OLS regression models

regressing bank’s financial (ROA), employee efficiency (EEF), Solvency efficiency (SEF), and deposit concentration (DP) on lagged Operational Risk

Disclosure Index (LRDI). The regression Model in Table 11.9 is as follows.

+ + + + + + + + + +

+ + + it

Where, Dependent variable is OPERF proxied as ROA, EEF, OEF and DP and independent variable is Lag_ERDI. ROA denotes Return on assets (calculated




value of assets divided by market value of assets). Lag_ERDI denotes Equity Risk Disclosure Index score (measured in Chapter five), BS denotes board size

(number of directors in the board), BS denotes board size (number of directors on the board), LnTA denotes bank size measured as total assets, BI denotes

board independence (proportion of independent directors on the board). GDP denotes GDP growth (official annual real GDP growth Figures in percentage

terms), CPI denotes inflation rate (official annual consumer price index in percentage terms) and DE denotes leverage, measured as debt to equity ratio.

Lag_ROA, Lag_EEF, Lag_OEF and Lag_DP are prior year lagged performance. ***, **, and * denote the level of significance at 1%, 5% and 10%,

respectively.

312


In this present research, content analysis of annual reports over the period from 2006-

2012 was reported in Chapter 7 to measure the extent of risk disclosure through the Risk

Disclosure Index and a score obtained for each of the banks in the sample. The

performance measures (return on asset, employee efficiency, solvency efficiency and

deposit concentration) were obtained directly from annual reports (2006-2012).

Bivariate and multivariate analyses were performed to test the relationship between the

hypothesised predictor variables and various measures of bank performance.

The findings of this study show a highly significant relationship between the lagged

Risk Disclosure Index score and financial performance (ROA), employee efficiency

(EEF) and marginal significance with solvency efficiency (SEF). However, no

relationship exists between the lagged Risk Disclosure Index and deposit concentration

(DP). The findings from this study also suggest bank market performance has a

significant relationship with the lagged Risk Disclosure Index. These findings underline

important associations between risk disclosure and banks performance. Moreover, the

associations between risk disclosure and bank performances (financial, employee

efficiency and Tobin’s q) are found to be stronger in Non-Islamic banks compared to

Islamic banks. The supplemental analysis in this Chapter also suggests that the Market

Risk Disclosure Index and lagged Equities Risk Disclosure Index is associated with

banks’ overall operating performance. In addition, governance indicators (board size,

independent boards) play a significant role in explaining variations in performance.

Governance components are also associated with bank market performance, indicating

the relation of governance on performance of banks in Bangladesh.

The supplemental analysis in this Chapter further examines the association of Market,

Credit, Liquidity, Operational and Equities Risk Disclosure with banks’ performances

and found financial performance, employee efficiency performance, and solvency

efficiency are associated with the lagged Market Risk Disclosure and Equities Risk

Disclosure Index. In addition, this study examines the relationship between High Risk

Disclosure and Low Risk Disclosure Groups with banks’ performance. The findings in

this study suggest that the lagged High Risk Disclosure Index has a positive association

313

with financial performance and employee efficiency performance. However, the lagged

Low Risk Disclosure Group has an association with deposit concentration.


This Chapter examines the relationship between the Risk Disclosure Index and banks’

performance. In this Chapter, both bivariate and multivariate analyses have been

performed to examine the association between bank financial performance, operating

efficiency, solvency efficiency, deposit concentration, Tobin’s q and book to market and

the lagged Risk Disclosure Index. The results support that the lagged Risk Disclosure

Index has an association with banks’ financial, solvency and employee efficiency. The

banks in the research sample are classified as High Risk Disclosers and Low Risk

Disclosers (see Table 11.5). The results suggest a significant association of High Risk

Disclosers with banks’ financial, employee efficiency and solvency efficiency. The next

Chapter provides the conclusion and implications of the study.

314

PART FIVE

CONCLUSION

Chapter 12: Conclusion and Implications

315

The final part presents a brief overview of the objectives of the study, summary of

research findings and implications, research contributions, limitations and future

research possibilities.

316

CHAPTER 12: Conclusion

12.1 Introduction

The purpose of this study was to investigate corporate risk information disclosed in the

Bangladesh banking industry. The country of Bangladesh is chosen as the focus for this

study came from a desire to understand the extent of risk disclosure practices in the

setting of a developing country. Bangladesh is aiming to become a middle-income

economy by the year 2021 (Vision 2021)65

. However, as discussed in Chapter 2, weak

institutional settings, poor legal structure and the autocratic nature of the International

Accounting Standard implementation process in the country, result in low level of

compliance in relation the accounting standards (Mir & Rahaman 2005; Sobhani,

Amran & Zainuddin 2012). Moreover, the lessons learned from the Western experience

hint that a lack of risk management and failure of governance mechanisms were key

contributing factors to the GFC of 2007-2008 (Aebi, Sabato & Schmid 2012; Erkens,

Hung & Matos 2012).

Bangladesh among the developing countries has started to implement International

Financial Reporting Standard (IFRS) 7 [Financial Instruments: Disclosures] and Basel

II: Market Discipline voluntarily66

. Of crucial importance, however, is the fact that

examining risk disclosure in a highly regulated environment would not provide the

insights of risk disclosure determinants because there would be little variation between

the actual and benchmark standard (IFRS 7 and Basel II: Market Discipline). In

addition, the interview data is used to support the assumption that Bangladesh offers a

unique setting due to the non-enforced nature of risk disclosure. As such, Bangladesh is

an ideal location for examining corporate entities can foster accountability and

transparency through the provision of corporate risk disclosure.

65

Bangladesh wants to be a middle-income country by 2021 (Ministry of Finance, Government of

Bangladesh (2014). The year 2021 will mark the golden jubilee of Bangladesh’s independence. 66

In the absence of mandatory requirements by company law or the Bank Company Act 1991, compliance

with International Financial Reporting Standards (IFRS) or Bangladesh Accounting Standards

(Bangladesh Financial Reporting Standards) is voluntary, as explained in Chapter 3.

317

The first Phase of the study involves examining corporate risk disclosure practices of all

listed banks in Bangladesh over a seven-year period (2006-2012). This is an important

period over which to examine corporate risk disclosure as it incorporates those years

impacted by the GFC (2007-2008). It is not the GFC per se but rather the reforms

triggered by the GFC might stimulus risk disclosure in financial reporting. A seven-year

time frame for this study provides valuable understandings concerning the monitoring

systems and governance mechanisms employed by banks on behalf of stakeholders. The

second Phase of the study investigates the determinants associated with banks’ risk

disclosure practices. The third and final Phase of the study investigates the association

of corporate risk disclosure with bank performance.

The objective of this Chapter is to provide a summary of the research findings for each

of these Phases and outline the contribution to the literature of this thesis and

implications that flow from the findings. Finally, the limitations of the research are

presented, followed by further directions within this area of research that could be

explored potentially in future research.

12.2 Overview

Three interrelated Phases are investigated in this broader study. Table 12.1 presents the

three-fold research objectives with the corresponding research Phases and findings.

318

62Table 12.1: This thesis’ research at a glance

Research Objectives Research Questions Hypothesis Phase

of the

study

Sources of Data Method Findings

1.To identify the extent of

corporate risk disclosure

practices in Bangladesh

listed banks’ annual reports

over a seven-year period

(2006-2012)

1: What is the extent of corporate

risk disclosure and to what extent

did banks in Bangladesh respond to

the development of international

standards (IFRS 7 and Basel II:

Market Discipline)?

H1: There are significant

differences in risk disclosure over

the period under examination,

2006-2012.

Phase

One

Company websites and

Bangladesh Securities

and Exchange

Commission.

Content

analysis

In aggregate,

there is an

increasing

trend under

the

examination

period.

2. To investigate the

determinants of corporate

risk disclosure

2: What firm characteristics and/or

institutional pressure act as

determinants for voluntary

disclosure of risks?

H2: The number of independent

directors on the board is associated

positively with the extent of risk

disclosure

H3: The number of independent

directors on the audit committee is

associated positively with the extent

of risk disclosure

H4: The number of risk committees

is positively associated with the

extent of risk disclosure.

H5: Coercive isomorphic pressures

are positively associated with the

extent of risk disclosure.

H6:Mimetic isomorphism of larger

banks influences smaller banks to

provide more risk disclosure.

H7: Normative isomorphism is

positively associated with the extent

of risk disclosure.

Phase

Two

1.Semi-structured

interviews with risk

reporting managers,

experts from the

Bangladesh Securities

and Exchange

Commission (BSEC)

and experts in the

policy development

department from the

Central Bank

(Bangladesh Bank)

2. Annual reports from

Dhaka Stock Exchange

Analysis

of semi-

structured

interviews,

t-tests,

correlation

s and

multiple

regression

H2, H4, H6

and H7

accepted

319

Research Objectives Research Questions Hypothesis Phase

of the

study

Sources of Data Method Findings

3. To examine the

association of corporate risk

disclosure with banks’

financial performance

3: Does corporate risk disclosure

have an association with bank

performance?

H8: Employee efficiency is


of risk disclosure.

H9: Solvency efficiency is


of risk disclosure.

H10: Deposit concentration is


of risk disclosure.

H11: Financial performance is


of risk disclosure.

H12: Bank value is positively

associated with the extent of risk

disclosure.

Phase

Three

Bank annual reports

from Dhaka Stock

Exchange

t-tests,

correlation

s and

multiple

regression

H8, H9, H11,

H12 (Tobin’s

q) accepted

320

Each Phase of the broader study has implications for the financial reporting literature as

it focuses on a specific financial reporting issue-that of risk related disclosure practices-

an area that has received little attention with limited research currently available

(Dobler, Lajili & Zéghal 2011; Woods & Linsley 2007). More specifically, this study

investigates the information banks provide in relation to their risk related corporate

governance practices- an issue that is yet to be investigated. As such, this study extends

the scope of research within corporate governance literature.

The underpinning theories (agency theory and institutional isomorphism) discussed in

Chapter 5, describe the conceptual framework for this study. These theories explain the

motivation of managers to provide corporate risk disclosure in the absence of

enforcement of compliance. As presented in Table 12.1, Phase One of the broader study

investigates the risk disclosure practices and provides a comprehensive, longitudinal

study of all 30 listed banks in Bangladesh over a seven-year period. An examination of

the banking sector is important as it holds more than 60 per cent share in the Gross

Domestic Product (GDP) (Bangladesh Bank 2013b). Thus, this study investigates a total

sample of 210 bank-year annual reports over 2006-2012.

A Risk Disclosure Index is developed consisting of 147 separate pieces of information

under seven general categories. The Risk Disclosure Index was constructed based on a

through and rigorous study of International Financial Reporting Standard [IFRS] 7:

Financial Instruments: Disclosures and BASEL II: Market Discipline. The RDI

includes both qualitative and quantitative information. Utilizing this Index as a

benchmark, this Phase employs content analysis of sample banks’ annual reports from

2006-2012 to examine and score the extent of risk disclosure over the period of

analysis. This is the first known study to provide a longitudinal study investigating the

disclosure behavior of banking companies in relation to risk related corporate

governance practices.

Phase One builds the foundation to investigate further in Phase Two. Phase Two

investigates what risk reporting-related experts (risk reporting managers in sample

banks and representatives from the Bangladesh Securities and Exchange Commission

321

and the Central Bank) perceive to be determining factors in relation to risk disclosure

(reported in Chapter 8). The hypothesised determinants associated with the extent of

risk disclosure within annual reports are tested, with results reported in Chapters 9 and

10. Thus, in Phase Two, using semi-structured interviews with banking and regulatory

representatives, this study aims to explore corporate insights in relation to corporate risk

reporting. Additionally, this study investigates the extent of risk disclosure and its

potential relationship with corporate characteristics, including board independence,

audit committee independence, the number of risk committees, and the debt to equity

ratio, total assets, and the presence of a risk management unit. This Phase utilises neo-

institutional isomorphism and agency theories to understand the factors underlying risk

disclosure. The theoretical implication is that since the experts consider the underlying

factors useful for assessing risk governance, they are is arguably the most relevant

knowledge for understanding what risk related governance factors are associated with

risk disclosure. In this Phase, the research approach uses thematic analysis of semi-

structured interviews and multiple regression analysis using data gathered from annual

reports. Research Question 2 is investigated based on a Hypotheses H2 to H7 (refer

Table 12.1), developed in Chapter 5 (Theoretical perspective underpinning the research:

Conceptual framework and hypotheses). This Phase employs a pooled OLS robust

regression model (Chapter 10) to examine the predictive ability of the variables

included in the model using the Risk Disclosure Index (developed in Phase One) to

score the dependent variable based on data from annual reports 2006-2012 for the

sample companies.

The third and final Phase of this research examines the potential association of risk

disclosure in relation to banks’ operating and market performance. Bank operating

performance is measured using financial performance, employee efficiency, solvency

efficiency, deposit concentration and bank market performance is measured using

Tobin’s q and the book to market ratio. Data for these performance measures are

derived from sample banks’ annual reports over the study period (2006-2012). This

Phase adopts an econometric approach (Chapter 11: The association between risk

322

disclosure and bank performance) to test the hypothesised67

relationships for 30 listed

banks in Bangladesh across the period 2006-2012.

12.3 Research findings and implications

The main findings and implications of the findings in each Phase are discussed as

follows.

1. The results of Phase One (Chapter 7) indicate that, in aggregate although there is an

increasing trend of risk disclosure over the period of analysis, there is a lack of risk

disclosure by sample banks in Bangladesh compared to the benchmark Risk disclosure

Index. The results highlight that while several risks are reasonably well disclosed, none

of the banks provide full disclosure of information identified in the Risk Disclosure

Index as best practice. Risk disclosure among Bangladesh listed banking companies is

found to be primarily focused on Internal Corporate Governance and General Risk

Information. Other categories identified in the Risk Disclosure Index, such as Risk Type

(Market, Credit, Liquidity, Operational and Equities), Capital Disclosure, Strategic

Decision and Governmental Regulation, showed little change over the sample period

despite the issuance of IFRS and Basel II. In addition, Non-Islamic banks on average

disclose more risk items compared to Islamic banks and the mean difference is

significantly different.

The implication of the research findings is that with the extent of disclosure being made

by sample companies, it is unlikely that banks’ stakeholders would gain an accurate

idea of the risk profile and the associated risks assessment and mitigation efforts,

relevant to particular banks. The findings from this research highlight the importance of

risk disclosure by banks and suggest that there is an opportunity for banks to increase

the extent of voluntary risk disclosure within their annual reports.

67

H7: Employee efficiency is positively associated with the extent of risk disclosure.

H8: Solvency efficiency is positively associated with the extent of risk disclosure.

H9: Deposit concentration is positively associated with the extent of risk disclosure.

H10: Financial performance is positively associated with the extent of risk disclosure.

H11: Bank value is positively associated with the extent of risk disclosure.

323

2. In Phase Two, the findings from interviews identified independent boards, the number

of risk committees, total assets and the presence of a risk management unit as important

determinants for risk disclosure. Moreover, quantitative data analysis from data

gathered from annual reports, also reveals that the underlying factors associated with

risk disclosure are the presence of an independent board (H2), the number of risk

committees (H4), total assets (H6) and the presence of a risk management unit (H7).

Hence, the results from this study from both qualitative and quantitative data confirm

the validity and importance of the determining factors associated with risk disclosure.

The findings for this Phase are more significant for Non-Islamic banks compared with

Islamic banks.

Further, the reasons for lack of corporate risk disclosure are identified in this Phase.

Based on the perspective of coercive isomorphism (as explained by institutional theory),

the interview data reveals a perceived lack of demand from stakeholders requiring more

information and banks not being motivated to disclose a great deal about risks. This

finding implies that a greater extent of risk disclosure depends on stakeholders

expressing concerns and their demands. In addition to a high level of demand from

stakeholders, the enforcement of international standards creates pressure that leads

banks to disclose more information.

Another reason for the lack of corporate risk disclosure is identified as the discretionary

nature of these disclosures. It can be argued that in absence of regulation and penalties

for non-compliance, banks do not disclose information. In addition to that, those banks

may lose credibility in the market and may not survive in future if they continue such

practices of low disclosure. Additionally, stakeholders’ (such as investors’) expectations

may be encouraged by recent development of international standards (IFRS 7 and

BASEL II) in relation to risk disclosure. As a result, banks that change their disclosure

behaviour may achieve competitive advantage over banks that do not.

Table 12.2 illustrates the confirmation of quantitative findings by the qualitative results;

the results confirm that the association between dependent and independent variables in

modelling risk disclosure in banking institutions in Bangladesh is well supported

324

statistically and conceptually. These factors are considered as key characteristics that

help drive listed banks in Bangladesh to achieve competitive advantage.

The interview data reveal unanticipated findings including about political interference,

lack of Central Bank autonomy, lack of accountability, demands by powerful

stakeholders, lack of education of investors and demand for brief and concise reports.

These findings support the arguments that data collection based on quantitative and

qualitative approaches can help improve both the reliability and validity of corporate

financial reporting research, and provide more insights into information concerning the

objectives under study. Table 12.2 presents the qualitative and quantitative findings in

relation to the predicted determinants of corporate risk disclosure.

Legend: * The variables are in brackets. DE denotes the debt equity ratio, LnTA denotes log

total assets, RMU denotes presence of a risk management unit, BI denotes board independence

measured as proportion of independent directors on the board. ACI denotes Audit Committee

Independence measured as the proportion of independent directors on the audit committee, RC

denotes number of risk committees.

As this stage, this Phase sheds light on risk governance factors. The findings will be

helpful for boards and managers of banks aiming to address their risk governance and

related disclosure practices. The findings will assist also annual report users who seek to

assess banks’ risk disclosure and how bank respond to these risks by evaluating the

information being disclosed by banks’ against the Risk Disclosure Index. These

Table 12.2: Quantitative findings’ confirmation of qualitative findings

Indicator variable for risk disclosure Quantitative Qualitative

Debt to Equity ratio (DE)* − −

Total Asset (LnTA) √ √

Risk Management Unit (RMU) √ √

Board independence (BI) √ √

Audit committee independence (ACI) − −

Risk committee (RC) √ √

325

findings have implications for regulators and standard setters searching for the best way

to shape policies and regulations regarding risk governance disclosure practices.

3. The third and final Phase of this research investigates the third Research Question

which examines the association between risk disclosure and bank performance. Bank

performance is measured using six aspects; financial performance, employee efficiency,

solvency efficiency, deposit concentration, Tobin’s q and book to market value. This

Phase employs a pooled OLS robust regression model to explain the association

between the Risk Disclosure Index and bank performance. The findings in this Phase

suggest significant association between the lagged Risk Disclosure Index and financial

performance, employee efficiency, solvency efficiency and Tobin’s q. However, no

relationship exists with deposit concentration and book to market. These findings

suggest that greater risk disclosure is an attempt to facilitate alignment of interests

between stakeholders and bank managers, which reduces agency costs and in turn is

associated with banks’ performance.

The three Phases of this study together provide a holistic picture to understand the

extent of risk disclosure practices, determinants and performances of all listed banks in

Bangladesh over a seven-year period (2006-2012).

12.4 Research contribution

The present research makes a significant contribution to the existing literature and to

knowledge in several ways as follows.

First, in an attempt to redress in part the empirical scarcity in risk disclosure studies in

developing countries, this study is the first to provide knowledge of corporate risk

disclosure practices, their underlying determinants and firm performance. This study

provides insights into risk disclosure practices by financial institutions and fills a gap in

the literature by providing a comprehensive and longitudinal study of corporate risk

disclosure information in banks’ annual reports in Bangladesh. The study investigates

financial statements and allows in-depth examination of trends and/or changes in

326

corporate risk disclosure over a seven-year period and reveals interesting insights to

better assess the risk disclosure of listed banks in Bangladesh. This research also

overcomes the gap that the corporate risk disclosure literature lacks an interrogative

framework that conceptualises multifaceted determinants of risk disclosure and the

significance of risk disclosure in relation to bank performance in developing countries.

The findings of this research, therefore, make a significant contribution to the literature

and provide a foundation for further research in this field.

Second, as mentioned in the previous section, in the first Phase of the study a unified

Risk Disclosure Index is developed in light of international standards (IFRS 7 and Basel

II) not required to be complied with by listed Bangladesh banks. The Risk Disclosure

Index is a comprehensive index that measures the extent of risk disclosure. This Index

covers many aspects of relevant information, such as risk assessment, risk strategies and

risk policies in relation to different types of risk (Market, Credit, Liquidity, Operational

and Equities). To the researcher’s knowledge, the Risk Disclosure Index developed in

this study is the first developed for the banking industry in measuring the extent of risk

information disclosed in annual reports. The Risk Disclosure Index contributes to the

literature and can be used to measure the level of risk disclosure practices in financial

institutions from other countries. This can also provide impetus to the recent debate on

risk disclosure practices among international standard setting bodies as they try to

harmonise their efforts. Additionally, the Risk Disclosure Index could be used as a

guideline/checklist for corporate risk disclosure and could be used as an early warning

system for banking institutions in any country.

Third, as discussed in the previous section, the second Phase of this study examines the

determinants of risk disclosure and utilises a distinctive conceptual model based on

agency and neo-institutional isomorphism theories. The empirical evidence from this

study validates the applicability of these theories. The findings suggests that

independent boards, the number of risk committees, debt to equity and the presence of a

risk management unit are significant factors in relation to corporate risk disclosure and

make a contribution to and provide practical implications for the application of agency

and neo-institutional isomorphism theories.

327

Fourth, the research tests the claim that enhanced risk information disclosed in

corporate annual reports is associated with banks’ better performance and finds this to

be the case for most measures of performance. Thus, this study adds to the existing

research on corporate risk disclosure. This result fills a gap in the existing literature by

testing empirically the association of risk disclosure with bank performance.

Fifth, this research makes significant contribution as the study goes one-step further by

examining risk disclosure practices, their determinants and the association of risk

disclosure with banks’ performance within the Islamic and Non-Islamic bank context.

Based on the assumption (refer to Chapter 1) that Islamic banks that follow Islamic

Shariah law might record different levels of corporate risk disclosure compared with

Non-Islamic banks, the study fills a gap in the existing literature by testing this issue

empirically. To the researcher knowledge, this is the first study to date to examine such

an association (risk disclosure practices, their determinants and the association of risk

disclosure with banks’ performance) using sub-samples from Islamic and Non-Islamic

banks. The findings reveal superior disclosures and performance by the non-Islamic

banks.

Sixth, this study also makes methodological contributions. It employs econometric

approaches to test hypotheses using longitudinal data gathered from annual reports and

interviews with bank managers and bank regulators (Bangladesh Central Bank and

Bangladesh Securities and Exchange Commission) to triangulate the results. Prior

literature on risk disclosure comprises mainly quantitative studies. Therefore, this

research generates rich data and permits a comprehensive understanding using a

triangulation strategy. Utilising a mixed methodology, this study integrates qualitative

(interview) methods and quantitative (econometric techniques applied to data from

annual reports) in examining the association between risk disclosure, its determinants

and performance. The interviews were employed to validate the findings from

secondary data and for providing richer information in relation to the research

objectives than could have been achieved by quantitative data alone, resulting in

strengthening the research findings and contributing to theory and knowledge

328

development. Therefore, the mixed data in this study provides a more complete

understanding of the issues being studied and enhances both reliability and validity of

this research compared to research that precedes it.

Finally, the findings can be generalised to some extent. The findings could be of interest

to other developing countries. Corporate risk disclosure has been validated to be

associated with bank performance for banks in Bangladesh, and possibly in countries

that follow similar transitional economic contexts.

12.5 Research limitations

While extending empirical knowledge in financial reporting and more specifically,

adding to prior disclosure studies in relation to risk disclosure practices, its determinants

and performance, this study is subject to some limitations. The limitations in this study

are follows.

First, one limitation of this study is related to use of the sampling unit, effectively listed

banks with available annual reports. The study focuses on risk disclosure only in annual

reports. However, banks employ other channels such as press releases, conference calls,

and websites. While this could be argued to be a limitation, nevertheless annual reports

are considered as the principal published document for communication (Linsley &

Shrives 2006).

A second limitation that must be acknowledged is related to the disclosure scoring

system. For example, instead of the extent of discussion or explanation, the score

equally weights each item in the Risk Disclosure Index. Therefore, items may not

reflect the level of importance as perceived by users of annual reports. In addition to

that must be acknowledged limitations in some measures (i.e. audit committee

effectiveness, risk committee effectiveness).

329

Third, this study uses semi-structured interviews with experts from within different

stakeholder groups (for example, bank managers, Bangladesh Central Bank, Bangladesh

Securities and Exchange Commission) to investigate banks’ risk disclosure practices,

their determinants and performance. The results of this Phase should be considered in

light of the usual methodological limitations inherent in a semi-structured interview

approach, including limited participant numbers and being perceptions-based, relying

on information provided by participants. This researcher also acknowledges that there is

a possibility that a free-rider problem may arise as users of banks’ annual reports

demand more than managers voluntarily disclose. Additionally, in-depth interviews are

useful for eliciting detailed information; however, limitations associated with it need to

be addressed. Interview responses cannot be estimated reliable by any statistical

measure, as their thoughts could be biased by various issues. For example, respondents

could attempt to hide the reality, may have faulty memories, and may have difficulties

with sequence or wording in the interview protocol. To minimise this possibility, the

researcher confirmed the confidentiality of the research, and informed the respondents

in advance about the discussion agenda.

Lastly, due to access, time constraints and political instability in Bangladesh during the

data collection period (February-April 2013), more specifically associated with the

interview data, the number of participants chosen from banks was limited, thereby

leading to a smaller sample size for interviews than had been planned.

12.6 Suggestions for future research

This study broadens the scope of financial accounting research by focusing on a specific

corporate risk governance issue – risk disclosure. In other words, it opens new research

areas in the voluntary disclosure literature by attempting to investigate risk disclosure

practices, their determinants and performance in an institutional setting where

compliance does not drive behaviour. The followings could be worthy of future research

that directly stem from this study.

330

1. Phase One of this study investigates the risk disclosure practices of listed banks in

Bangladesh. Although this research analyses the disclosure practices of all listed banks,

further research could utilise the Risk Disclosure Index on all other financial (for

example, insurance, leasing, mortgage) and other manufacturing companies, both in

Bangladesh and rest of the world, adapted if necessary, in order to investigate whether

findings can be applied more broadly within other industries. Such investigation would

extend the robustness and applicability of the Risk Disclosure Index, which is arguably

the most comprehensive index developed to-date in relation to risk disclosure practices.

In addition, future research can also employ the Risk Disclosure Index to compare the

disclosure practices of the companies in different contexts (for example, developed vs.

developing countries). This comparative study appears relevant and important for future

research given growing attention on the issue of risk governance.

2. The second Phase of the broader study provides results generated by conducting in-

depth interviews with managers from some of the sample banks and experts from the

Central Bank and the Bangladesh Securities and Exchange Commission. They discussed

the research questions, however; more insights could be derived by conducting

interviews with a greater number of respondents from all the sample banks or from non-

listed banks. Future study can pursue this possibility of research to make an even deeper

understanding of risk governance issues.

3. This research has found a perceived lack of demand from stakeholders’ by the

interviewees from the qualitative data. It would help reveal whether, and if so why,

stakeholder force is not existent by understanding the contexts provided by them, such

as institutional investors and government. In-depth interviews with stakeholder groups

would be helpful in gaining a greater insight into their expectations and activities, such

as collaboration with or confrontation with banks with respect to risk disclosure

practices.

4. This study provides a platform for future research that can be developed further in

relation to banks’ risk governance issues. In the light of significant challenges in the

global economy, this study inspires other researchers to follow this possibility of

331

investigation, more specifically, to find out risk disclosure reactions to implementation

of international standards.

333

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Appendices

Appendix 6.1: Paradigmatic dichotomies in research

Authors The philosophy of financial research

Veal

(2005, pp.

24-29)

Positivist-

Interpretive

Positivist-Positivist

paradigms view the

objectivity to the researcher,

and are referred to also as

scientific, empiricist,

quantitative or deductive.

Interpretive/Critical- Interpretive

paradigms view the subjectivity

to the researcher followed by

inductive qualitative method.

Quantitative

and qualitative

Quantitative- involves

gathering and analysis of

numerical data using the

primary sources such as

questionaries survey,

observation or from

secondary sources to

generalise the results in

whole population.

Qualitative- involve relatively

small number of sample using

observation, informal,

unstructured and in depth

interview and findings are not

typically generalizable.

Induction and

Deduction

Induction- begins with

observation, description and

data collection to explain the

theoretical proposition.

Deduction- begins with

hypothesis and tests the

hypothesis.

Experimental

and Non-

experimental

Experimental-

Research conducted in an

environment (e.g. laboratory)

in which the researcher has a

control over a limited number

of variables.

Non-experimental

Research conducted in a ‘real

world’ environment where the

researcher has no control over

variables.

Ryan et

al(2002,

pp.34-36)

Alternative philosophies of Accounting Research

Scientific-

naturalistic

Scientific- starts from a well-

formulated theory, usually

derived from a review of the

previous academic literature

and expressed in the form of

mathematical model, the

theory used to formulate

hypotheses that express

relationship between sets of

dependent and independent

variables.

Naturalistic- appropriate for

studying the everyday behaviour

to study research subjects in

their natural settings; based on

realism, holism and analytical

method like case study.

352

Appendix 6.2: Types of research from the viewpoint of different

perspectives Authors Viewpoint Types of research

Kumar

(2011,p.10-

14)

Application

perspective

Pure- developing theories and hypothesis containing

abstract and specialised concept.

Applied- research techniques, procedures and methods

that form the body of research methodology are applied

to the collection of information to understand the

phenomenon.

Objectives

perspective

Descriptive-describes the phenomena as they exists,

quantitative data and statistical techniques are used to

summarise the information (Collis & Hussey 2003).

Correlational-emphasis is to discover or establish the

existence of a relationship/association/interdependence

between two or more aspects of a situation.

Explanatory-clarify why and how there is a relationship

between two aspects of a situation or phenomenon.

Exploratory-conducted when there are very few studies

and aims to look for patterns, ideas or propositions rather

than to tests or confirm hypothesis. (Collis & Hussey

2003)

Enquiry

mode

perspective

Structured-Objectives, design, sample, and the

questions to respondents are predetermined and usually

classified quantitative research.

Unstructured-allows flexibility to explore the nature,

variation/diversity per se in a phenomenon, issue,

problem, or attitude towards an issue and usually

classified as qualitative approach.

Collis and

Hussey

(2003,p.10-

12)

Exploratory, Descriptive, Analytical or explanatory

and

Predictive –aims to generalise from the analysis by

predicting certain phenomenon on a basis of

hypothesised, general relationships.

Veal

(2005,p.4-5)

Descriptive, Explanatory, Exploratory and

Evaluative- arises from the need to make judgements on

the success or effectiveness of policies practices,

strategies or programs.

353

Appendix 6.3: Mixed method research design

Author Types Definition

Creswell

and Clarke

(2011, p.73)

Convergent Design Concurrent quantitative and

qualitative data collection,

separate quantitative and

qualitative analysis, and the

merging of the two data sets.

Explanatory Design Methods implemented

sequentially, starting with

quantitative data collection and

analysis followed by qualitative

data collection and qualitative data

collection and analysis.

Exploratory Design Methods implemented

sequentially, starting with

qualitative data collection and

analysis followed by quantitative

data collection and analysis.

Embedded Design Either the concurrent or sequential

collection of supporting data with

separate data analysis or the use of

the supporting data before, during,

or after the major data collection

procedure.

Transformative Design Framing the concurrent or

sequential collection and analysis

of quantitative and qualitative data

sets within a transformative,

theoretical framework that guides

the methods decision.

Multiphase Design Combining the concurrent and/or

sequential collection of

quantitative and qualitative data

sets over multiple phases of a

program of study.

Teddlie and

Tashakkori

(2009)

Concurrent/parallel/simultaneous

Sequential Design

Similar to Convergent design

Explanatory or exploratory design

Creswell

(2003) Transformative

Concurrent

Sequential

‘In transformative procedure

researcher uses a theoretical lens

as an overarching perspective

within a design that contains both

qualitative and quantitative

data…..this lens could be a data

collection method that involves a

sequential and concurrent

approach’ (p.16).

354

Appendix 6.4: Interview protocol

Section A: Introduction

This section requires you to complete some basic background information about

yourself. Please circle the appropriate option

1. Your gender is

a. Male

b. Female

2. What is your age group

a. 25-35

b. 36-45

c. 46-55

d. 56-65

3. What is your level of education

a. Up to College

b. Bachelor Degree or equivalent

c. Postgraduate (Masters) Degree or equivalent

d. Professional course; such as ACMA, CA, ACCA

e. PhD

4. Number of years worked for/in Banks

a. Less than 1 year

b. 1-5 years

c. 6-10 years

d. 11-15 years

e. 15-20 years

f. More than 20 years

355

Section B

Regulators and financial experts

A. Are current corporate risk management practices effective at assessing risk?

To what extent the risk disclosures items are effective in practice for banks in

Bangladesh?

B. Do you have any comments on the proposed risk disclosure guideline?

C. Did the Global Financial Crisis (GFC) of 2007-2008 uncover weaknesses in

governance mechanism in banking sector of Bangladesh?

D. Did GFC of 2007-2008 uncover inadequacy of corporate risk disclosure in

banking sector of Bangladesh?

E. Does corporate governance have an impact on risk disclosures practices in

the banking sector in Bangladesh?

F. Did the GFC have an impact on banking sector in Bangladesh? In the light of

financial crisis what regulatory changes you suggest for the banking sector in

Bangladesh?

G. How should banks be intensified to implement effective risk management

frameworks? Is more prescriptive regulation or any other alternatives? (i.e.

improved disclosure, changing corporate governance, enhanced rating

methodologies etc)

H. Do you have any other comments?

Thank you for your Time

356

Appendix 6.5: Consent form

INTERVIEW PARTICIPANT INFORMATION AND CONSENT FORM (PICF)

Thesis Title: Risk Disclosures Practices, Corporate Governance and Bank’s Performance: Evidence

from a developing country

Investigator(s): Dr Mohammad Azim Dr Ron Kluvers Shamsun Nahar

Project Interests

This research is to investigate the possible link between the governance mechanism and

level of risk disclosures practices in banking sector and their effect on performance. The

interview will examine the degree of compliance of banks with their commendation of

code of corporate governance, risk disclosure practice and the performance of banks in

pre-recession to post recession period. Data from this research will identify the drivers

of corporate risk reporting best practices by banks in Bangladesh and establish firm

specific or corporate governance characteristics that are related to the risk reporting and

also the impact of risk reporting on bank’s performance.

What participation will involve?

Participation in the project is completely anonymous and voluntary. It should take

participants approximately 30-45 minutes complete the interview. Participants who

agree to participate in the interview will be required to sign a consent form attached.

Research Output:

The data gathered will be used for this thesis and will be used to develop conference

papers for academic journals. The researcher will be the only person to have access to

your responses. Participants will not be identified in the analysis or subsequent

publications.

Further information about the project

Should you require any further information about this project please do not hesitate to

contact us

Shamsun Nahar, PhD student

Email : [email protected] ph: (+61) 3 92145247

Dr Mohammad Azim

Email: [email protected] ph: (+61) 3 92144500

Dr Ron Kluvers

Email: [email protected] ph: (+61) 3 92148435

mailto:[email protected]



357

Informed consent to participate in research:

Please read and sign

1. I consent to participate in the project named above. I have been provided a copy of

the project consent information statement to which this consent form relates and any

questions I have asked have been answered to my satisfaction.

2. In relation to this project, please circle your response to the following:

I agree to be interviewed by the researcher Yes No

I agree to allow the interview to be recorded by electronic device Yes No

I agree to make myself available for further information if required Yes No

I agree to complete questionnaires asking me about

[insert topic(s)] Yes No

3. I acknowledge that:

(a) my participation is voluntary and that I am free to withdraw from the project at

any time without explanation;

(b) the Swinburne project is for the purpose of research and not for profit;

(c) any identifiable information about me which is gathered in the course of and as

the result of my participating in this project will be (i) collected and retained for

the purpose of this project and (ii) accessed and analysed by the researcher(s) for

the purpose of conducting this project;

(d) my anonymity is preserved and I will not be identified in publications or

otherwise without my express written consent.

By signing this document I agree to participate in this project.

Name of Participant: …………………………………………

Signature & Date: ……………………………………………

358

Appendix 6.6 : Ethics Approval Letter

Dear Shamsun,

Your response was forwarded to a delegate and the following feedback has been

received. Your application has bee approved except for the following further

amendments to be made:

5. Appendix 5, Organisational Informed Consent Form:

1, second dot point - please redraft this statement for better effect as follows -

Instead of “I agree that s/he can be interviewed by the researcher” replace with

words along the lines of ”I agree for my employees to be interviewed for this project”

Your response to C9 needs revisions as follows:

3. C9:

(i) Interviews need to take place in a business location

(ii) Please explain the arrangements to be put in place to ensure safety of student

researcher;

As you have stated that the interviews will take place in a business location this has

satisfied the Subcommittee’s concern on this matter more the most part, however,

1. the delegate suggests you may wish also to ensure that a supervisor is informed

about times and locations of the interviews as a further safety measure. This

should, therefore, be included in this paragraph.

2. Please also delete the remaining sentences as it is not about your safety in your

office at Swinburne which you were asked to address.

Please amend C9 as outlined about and send me the revised Consent Form for my file. I

will then be able to issue the clearance.

Regards

Kaye

From: Shamsun Nahar

Sent: Tuesday, 29 January 2013 12:04 PM

To: Kaye Goldenberg

Subject: SUHREC Project 2012/270 Ethical Review of Resubmtted Protocol

Dear Kaye

The concern has been revised. Please find the attachments.

Thanks and Kind regards

Shamsun

PhD candidate

Faculty of Business Enterprise

AGSE building, level 3

Room 340,ph-92145247

359

From: Kaye Goldenberg

Sent: Friday, 25 January 2013 4:52 PM

To: Mohammad Azim; Shamsun Nahar

Subject: SUHREC Project 2012/270 Ethical Review of Resubmtted Protocol

To: Dr Mohammad Azim, Design/ Ms Shamsun Nahar

Dear Dr Azim,

SUHREC Project 2012/270 Risk Disclosure Practices, Corporate Governance and

Bank’s Performance: Evidence from Bangladesh Proposed Duration From: 10/01/2013

Proposed Duration To: 30/07/2015

Ethical review of the above project protocol as resubmitted/revised, was undertaken on

behalf of Swinburne's Human Research Ethics Committee (SUHREC) by a SUHREC

Subcommittee (SHESC1) at a meeting held 18 January 2013, the outcome of which as

follows.

The project has been approved subject to the following being addressed to the Chair (or

delegate's) approval:

1. C2:

(i) Please provide more information on the recruitment procedures, for instance, who

will participants contact regarding arranging the interviews?

a) Please also explain in detail how recruitment will be carried out within the

organisation;

(ii) Please explain the relevance of the first sentence of the second last paragraph, in

particular, who are the “regulators and educators’?;

2. C4: It is unnecessary to tick the second box. Please uncheck;

3. C9:

(i) Interviews need to take place in a business location

(ii) Please explain the arrangements to be put in place to ensure safety of student

researcher;

4. Interview Agenda, Section B,

(i) Question A: Suggest amending first sentence as follows – “To what extent are

current….”

a) Amend second sentence to clarify meaning.

(ii) Question F: Please clarify what is meant by ‘intensified’ in this context? Should the

word be ‘encouraged’?

5. Appendix 5, Organisational Informed Consent Form: As the Subcommittee felt that it

was not appropriate to reveal the identity of the employees it is recommended that the

form be redrafted by -

(i) removing the reference to the name of the individual employee in Section 1 and

(ii) using only a blanket reference to employees in Section 2,

Re your responses:

- please DO NOT submit a full revised ethics clearance application unless specifically

required

- queried, missing, additional or revised text from the ethics application can be

incorporated into your responses (within the body of the email if appropriate and to save

360

disk space)

- attach proposed or revised consent/publicity/other instruments in light of the above (if

available, converting these documents to pdf before submission will disk space)

If accepted by the SUHREC or Subcommittee delegate(s), your responses/attachments

will be added to previous documentation submitted for review, superseding or

supplementing the existing material/protocol on record. Please also note that human

research activity (including active participant recruitment) cannot commence before

proper ethics clearance is given in writing.

Please contact me if you have any queries about the ethical review process undertaken.

The SUHREC project number should be quoted in communication.

Yours sincerely

Kaye Goldenberg

Secretary, SHESC1

*******************************************

Kaye Goldenberg Administrative Officer (Research Ethics)

Swinburne Research (H68)

(Mon, Tues, alt.Thurs. Fri.) Swinburne University of Technology

Level 1, SPS, 24 Wakefield Street

Hawthorn, VIC 3122

Tel: +61 3 9214 8468

Fax: +61 3 9214 5267

361

Appendix 7.1 Tukey HSD: RDI by year

Year

Sig.

I

J

2006

2007 2008 2009 2010 2011 2012

2006 0.641

2007

0.641

0.971 0.008*** .000** .000** .000**

2008

0.971 0.971 0.077*** .000** .000** .000**

2009

0.008*** 0.008*** 0.077*** 0.117 0.001** .000**

2010

.000** .000** .000** 0.117 0.639 0.458

2011

.000** .000** .000** 0.001** 0.639

1.00

2012

.000** .000** .000** .000** 0.458 1.00


362

Appendix 7.2: Eta Squared

The guideline proposed by Cohen (1988, pp. 284-7 for interpreting the values is

.01= small effect, .06= moderate effect, .14= large effect

t t^2 N Eta squared=

T^2/T^+(N-1)

Effect

-2.706 7.322 30 0.201 Large effect

-5.732 32.855 30 0.531 Large effect

-2.921 8.532 30 0.227 Large effect

363

Appendix 9.1: Post Hoc Tukey P value

DE TA RMU BS BI ACI ML RC Age

Dependent

Variable

(I)

Year

(J)

Year

Sig.

2006 2007 1.00 0.27 0.62 0.77 0.81 1.00 1.00 0.83 0.75

2008 1.00 0.86 0.00 0.97 0.87 0.20 1.00 0.28 0.99

2009 0.98 0.24 0.00 0.77 1.00 0.11 1.00 0.01 0.86

2010 1.00 0.01 0.00 0.80 0.97 0.07 1.00 0.00 0.53

2011 0.82 0.00 0.00 0.58 0.38 0.04 1.00 0.00 0.37

2012 0.96 0.00 0.00 0.28 0.66 0.15 1.00 0.00 0.43

2007 2006 1.00 0.27 0.62 0.77 0.81 1.00 1.00 0.83 0.75

2008 1.00 0.36 0.72 0.97 0.91 1.00 1.00 0.93 0.98

2009 1.00 0.03 0.00 0.60 0.26 0.27 1.00 0.03 0.78

2010 0.96 0.00 0.00 0.28 0.66 0.15 1.00 0.00 0.43

2011 1.00 0.00 0.00 0.31 0.47 0.10 1.00 0.00 0.16

2012 0.73 0.00 0.00 0.15 0.04 0.05 1.00 0.00 0.09

2008 2006 1.00 0.27 0.62 0.77 0.81 1.00 1.00 0.83 0.75

2007 1.00 0.36 0.72 0.97 0.91 1.00 1.00 0.93 0.98

364

2009 1.00 0.86 0.00 0.97 0.87 0.20 1.00 0.28 0.99

2010 0.98 0.24 0.00 0.77 1.00 0.11 1.00 0.01 0.86

2011 1.00 0.01 0.00 0.80 0.97 0.07 1.00 0.00 0.53

2012 0.82 0.00 0.00 0.58 0.38 0.04 1.00 0.00 0.37

2009 2006 1.00 0.27 0.62 0.77 0.81 1.00 1.00 0.83 0.75

2007 1.00 0.03 0.00 0.60 0.26 0.27 1.00 0.03 0.78

2008 1.00 0.86 0.00 0.97 0.87 0.20 1.00 0.28 0.99

2010 1.00 0.90 0.90 1.00 0.99 1.00 1.00 0.67 0.99

2011 1.00 0.13 0.90 1.00 1.00 1.00 1.00 0.14 0.88

2012 0.94 0.05 0.90 0.96 0.96 0.98 1.00 0.07 0.76

2010 2006 1.00 0.27 0.62 0.77 0.81 1.00 1.00 0.83 0.75

2007 0.96 0.00 0.00 0.28 0.66 0.15 1.00 0.00 0.43

2008 0.98 0.24 0.00 0.77 1.00 0.11 1.00 0.01 0.86

2009 1.00 0.90 0.90 1.00 0.99 1.00 1.00 0.67 0.99

2011 0.99 0.71 1.00 1.00 1.00 1.00 1.00 0.93 0.99

2012 0.99 0.48 1.00 1.00 0.69 1.00 1.00 0.80 0.97

2011 2006 1.00 0.27 0.62 0.77 0.81 1.00 1.00 0.83 0.75

365

2007 1.00 0.00 0.00 0.31 0.47 0.10 1.00 0.00 0.16

2008 1.00 0.01 0.00 0.80 0.97 0.07 1.00 0.00 0.53

2009 1.00 0.13 0.90 1.00 1.00 1.00 1.00 0.14 0.88

2010 0.99 0.71 1.00 1.00 1.00 1.00 1.00 0.93 0.99

2012 0.87 1.00 1.00 1.00 0.85 1.00 1.00 1.00 1.00

2012 2006 1.00 0.27 0.62 0.77 0.81 1.00 1.00 0.83 0.75

2007 0.73 0.00 0.00 0.15 0.04 0.05 1.00 0.00 0.09

2008 0.82 0.00 0.00 0.58 0.38 0.04 1.00 0.00 0.37

2009 0.94 0.05 0.90 0.96 0.96 0.98 1.00 0.07 0.76

2010 0.99 0.48 1.00 1.00 0.69 1.00 1.00 0.80 0.97

2011 0.87 1.00 1.00 1.00 0.85 1.00 1.00 1.00 1.00

366

Appendix 9.2: Eta Squared

Formula ML RMU Effect*

=.0384

= .3137

.01= small effect

.06=moderate

effect

.14= large effect

Small effect Large effect

*guidelines proposed by Cohen 1988, pp. 284-7

367

Appendix 10.1 (A-E). Correlation for Five sub categories of risk disclosures

10.1 A: Pearson Correlation Credit Risk Disclosure Index for pooled data (2006-2012) (N=210)

***, **, and *denote the level of significance at 1%, 5% and 10%, respectively.

CRDI DE LnTA RMU LnBS BI ACI ML RC LnAG

CRDI 1.000

DE -0.019 1.000

LnTA 0.458

** 0.137 1.000

RMU 0.577

** -0.077 0.244

** 1.000

LnBS 0.184

* 0.202

** 0.324

** 0.130 1.000

BI 0.203

** -0.108 0.083 0.216

** -0.159

* 1.000

ACI 0.334

** -0.107 0.187

* 0.430

** 0.051 0.304

** 1.000

ML 0.222

** -0.129 0.074 0.119 -0.313

** 0.190

* 0.123 1.000

RC 0.299

** 0.094 0.165

* 0.474

** 0.038 0.269

** 0.331

** -0.097 1.000

LnAG 0.044 -0.130 0.263

** -0.051 -0.022 -0.036 -0.105 0.144 -0.009 1.000

368

10.1 B: Pearson Correlation Liquidity Risk Disclosure Index for pooled data (2006-2012) (N=210)

LRDI DE LnTA RMU LnBS BI ACI ML RC LnAG

LRDI 1.000

DE 0.032 1.000

LnTA 0.373

** 0.137 1.000

RMU 0.365

** -0.077 0.244

** 1.000

LnBS 0.108 0.202

** 0.324

** 0.130 1.000

BI 0.333

** -0.108 0.083 0.216

** -0.159

* 1.000

ACI 0.295

** -0.107 0.187

* 0.430

** 0.051 0.304

** 1.000

ML 0.220

** -0.129 0.074 0.119 -0.313

** 0.190

* 0.123 1.000

RC 0.322

** 0.094 0.165

* 0.474

** 0.038 0.269

** 0.331

** -0.097 1.000

LnAG 0.291

** -0.130 0.263

** -0.051 -0.022 -0.036 -0.105 0.144 -0.009 1.000


369

10.1 C: Pearson Correlation Market Risk Disclosure Index for pooled data (2006-2012) (N=210)

MRDI DE LnTA RMU LnBS BI ACI ML RC LnAG

MRDI 1.000

DE 0.014 1.000

LnTA 0.375

** 0.137 1.000

RMU 0.568

** -0.077 0.244

** 1.000

LnBS 0.147

* 0.202

** 0.324

** 0.130 1.000

BI 0.131 -0.108 0.083 0.216

** -0.159

* 1.000

ACI 0.328

** -0.107 0.187

* 0.430

** 0.051 0.304

** 1.000

ML 0.145 -0.129 0.074 0.119 -0.313

** 0.190

* 0.123 1.000

RC 0.356

** 0.094 0.165

* 0.474

** 0.038 0.269

** 0.331

** -0.097 1.000

LnAG 0.056 -0.130 0.263

** -0.051 -0.022 -0.036 -0.105 0.144 -0.009 1.000


370

10.1 D: Pearson Correlation Operational Risk Disclosure Index for pooled data (2006-2012) (N=210)

ORDI DE LnTA RMU LnBS BI ACI ML RC LnAG

ORDI 1.000

DE 0.001 1.000

LnTA 0.120 0.137 1.000

RMU 0.069 -0.077 0.244** 1.000

LnBS 0.102 .202** 0.324** 0.130 1.000

BI -0.078 -0.108 0.083 0.216** -0.159* 1.000

ACI -0.069 -0.107 0.187* 0.430** 0.051 0.304** 1.000

ML -0.133 -0.129 0.074 0.119 -0.313** 0.190* 0.123 1.000

RC -0.043 0.094 0.165* 0.474** 0.038 0.269** .331** -0.097 1.000

LnAG 0.027 -0.130 0.263** -0.051 -0.022 -0.036 -0.105 0.144 -0.009 1.000


371

10.1 E: Pearson Correlation Equities Risk Disclosure Index for pooled data (2006-2012) (N=210)

ERDI DE LnTA RMU LnBS BI ACI ML RC LnAG

ERDI 1.000

DE -0.004 1.000

LnTA 0.372

** 0.137 1.000

RMU 0.379

** -0.077 .244

** 1.000

LnBS 0.056 0.202

** .324

** 0.130 1.000

BI 0.296

** -0.108 0.083 0.216

** -0.159

* 1.000

ACI 0.325

** -0.107 0.187

* 0.430

** 0.051 0.304

** 1.000

ML 0.157

* -0.129 0.074 0.119 -0.313

** 0.190

* 0.123 1.000

RC 0.313

** 0.094 0.165

* 0.474

** 0.038 0.269

** 0.331

** -0.097 1.000

LnAG 0.122 -0.042 -0.239

** 0.041 -0.092 0.159

* 0.102 0.040 0.084

DE 0.117 -0.130 0.263

** -0.051 -0.022 -0.036 -0.105 0.144 -0.009 1.000


372

Appendix 10.2: Pearson correlations change Risk Disclosure Index (RDI) 2006 and 2008 (N=60)

Change

RDI

2006_2008

Change

BI

2006_2008

Change

ACI

2006_2008

Change

RC

2006_2008

Change

DE

2006_2008

Change

LnTA

2006_2008

Change

RMU

2006_2008

Change

LnBS

2006_2008

Change

ML

2006_2008

Change

LnAG

2006_2008

Change RDI 2006_2008 1.000

Change BI 2006_2008 -0.074 1.000

Change ACI 2006_2008 0.007 0.081 1.000

Change RC 2006_2008 0.061 -0.030 0.018 1.000

Change DE 2006_2008 -0.013 -0.332** -0.205* 0.095 1.000

Change LnTA 2006_2008 -0.068 0.142 -0.085 -0.141 0.001 1.000

Change RMU 2006_2008 0.061 0.062 0.308** 0.311** -0.034 -0.099 1.000

Change LnBS 2006_2008 0.144 -0.057 0.229** -0.003 0.029 0.033 0.075 1.000

Change ML 2006_2008 -0.150 0.052 0.115 -0.036 0.009 0.211** -0.059 -0.142 1.000

Change LnAG 2006_2008 0.043 0.001 -0.011 -0.124 0.016 0.158 -0.075 0.099 0.021 1.000


373


Change

RDI

2006_2012

Change

BI

2006_2012

Change

ACI

2006_2012

Change

RC

2006_2012

Change

DE

2006_2012

Change

LnTA

2006_2012

Change

RMU

2006_2012

Change

LnBS

2006_2012

Change

ML

2006_2012

Change

LnAG

2006_2012

Change RDI 2006_2012 1.000

Change BI 2006_2012 0.127 1.000

Change ACI 2006_2012 -0.021 0.301 1.000

Change RC 2006_2012 -0.125 0.398* 0.032 1.000

Change DE 2006_2012 -0.015 -0.466**

-0.423* 0.076 1.000

Change LnTA 2006_2012 0.220 -0.255 -0.127 -0.238 0.225 1.000

Change RMU 2006_2012 -0.103 0.257 0.286 0.072 -0.236 -0.156 1.000

Change LnBS 2006_2012 0.037 0.012 -0.033 0.189 0.163 -0.033 0.035 1.000

Change ML 2006_2012 0.072 -0.038 0.177 -0.426* -0.227 0.093 -0.304 -0.252 1.000

Change LnAG 2006_2012 0.001 -0.147 -0.128 -0.251 0.120 0.475**

-0.169 0.208 0.109 1.000


374


Change

RDI

2006_2010

Change

BI

2006_2010

Change

ACI

2006_2010

Change

RC

2006_2010

Change

DE

2006_2010

Change

LnTA

2006_2010

Change

RMU

2006_2010

Change

LnBS

2006_2010

Change

ML

2006_2010

Change

LnAG

2006_2010

Change RDI 2006_2010 1.000

Change BI 2006_2010 0.073 1.000

Change ACI 2006_2010 -0.050 0.145 1.000

Change RC 2006_2010 -0.092 0.073 -0.105 1.000

Change DE 2006_2010 0.083 -.378**

-0.269* 0.227

* 1.000

Change LnTA 2006_2010 0.038 -0.107 -0.088 -0.268* -0.101 1.000

Change RMU 2006_2010 -0.144 0.226* 0.232

* 0.236

* -0.033 -0.245

* 1.000

Change LnBS 2006_2010 0.103 -0.182 0.065 0.068 0.087 -0.078 0.091 1.000

Change ML 2006_2010 -0.016 0.001 0.152 -0.311**

-0.215* 0.265

* -0.270

** -0.232

* 1.000

Change LnAG 2006_2010 0.097 -0.061 -0.102 -0.232* 0.018 0.387

** -0.259

* 0.164 0.067 1.000


375


Change

RDI

2010_2012

Change

BI

2010_2012

Change

ACI

2010_2012

Change

RC

2010_2012

Change

DE

2010_2012

Change

LnTA

2010_2012

Change

RMU

2010_2012

Change

LnBS

2010_2012

Change

ML

2010_2012

Change

LnAG

2010_2012

Change RDI 2010_2012 1.000

Change BI 2010_2012 0.117 1.000

Change ACI 2010_2012 -0.011 0.201 1.000

Change RC 2010_2012 -0.124 0.328 0.142 1.000

Change DE 2010_2012 -0.011 -0.366 -0.223 0.176 1.000

Change LnTA 2010_2012 0.120 -0.455 -0.1257 -0.258 0.225 1.000

Change RMU 2010_2012 -0.143 0.247 0.246 0.452 -0.236 -0.156 1.000

Change LnBS 2010_2012 0.047 0.112 0.253 -0.450 0.164 -0.033 0.035 1.000

Change ML 2010_2012 0.072 -0.038 0.257 -0.436 -0.227 0.093 -0.304 -0.252 1.000

Change LnAG 2010_2012 0.001 0.001 -0.167 -0.148 -0.251 0.120 0.475 -0.169 0.208 1.000

***, **, and * denote the level of significance at 1%, 5% and 10%, respectively

shamsun nahar msc (accounting and finance), uk m.b.a, b.b

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