IMPACT OF INTEREST RATE SPREAD ON PROFITABILITY OF

COMMERCIAL BANKS IN NEPAL

BY

PARITOSH POUDEL

Roll no: 14472/14

TU Registration number: 7-2-22-16-2014

A summer project report submitted to

Faulty of Management, Tribhuvan University

In partial fulfillment of the requirement for the degree of

Bachelors of Business Administration

at the

Patan Multiple Campus

Tribhuvan University

Patandhoka, Lalitpur

May, 2018

ii

RECOMMENDATION BY SUPERVISOR

This is to certify that the summer project entitled “IMPACT OF INTEREST RATE

SPREAD ON PROFITABILITY OF COMMERCIAL BANKS IN NEPAL” is an

academic work done by “ Mr. Paritosh Poudel” submitted in the partial fulfillment of the

requirement for the degree of Bachelor of Business Administration” at faculty of

Management; Tribhuvan University under my guidance and supervision. To the best of my

knowledge, the information presented by him in the summer project report has not been

submitted earlier.

Signature of supervisor

Bijaya Gopal Shrestha

Professor

May, 2018

iii

VIVA - VOCE SHEET

We have conducted the viva - voce examination of the summer project report presented by

Paritosh Poudel

Patan Multiple Campus

Patandhoka, Lalitpur

TU Registration Number: 7-2-22-16-2014

Entitled

IMPACT OF INTEREST RATE SPREAD ON PROFITABILITY OF

COMMERCIAL BANKS IN NEPAL

And found the report to be original work of the student and written according to the

prescribed format. We recommend the report to be accepted as partial fulfillment of the

requirements for the degree of

Bachelor of Business Administration (BBA)

Head, Research Department:………………………….

Member (Report Supervisor):…………………………

Member (External Expert):……………………………

Date:…..…………………………………………………

iv

STUDENTS DECLARATION

This is to certify that I have completed the summer project entitled “Impact of interest rate

spread on profitability of commercial banks in Nepal” under the guidance of Prof. Bijaya

Gopal Shrestha in partial fulfillment of the requirement for the degree of Bachelor of

Business Administration at Faculty of Management, Tribhuvan University. This is my

original work and I have not submitted it earlier elsewhere.

(………………………….)

Paritosh Poudel

Class Roll no:14472/2014

v

ACKNOWLEDGEMENTS

This research entitled “Impact of interest rate spread on profitability of commercial

banks in Nepal” been prepared for partial fulfillment of Bachelor of Business

Administration. It is directed to find out the relationship between capital structure and

capital structure of commercial banks of Nepal.

I would like to express my deep sense of gratitude to the faculty members of Patan

Multiple Campus who fully support to make it easy for completing this project. My

limitless thanks goes to my supervisor Prof. Bijaya Gopal Shrestha and BBA Director

Dr.Yuga Raj Bhattarai ,the leading faculty of our campus, for painstakingly seeing me

through the arduous task of Bachelor level in Management studies, and also for his

unflinching support and relentless advice to ensure the completion of the project of my

studies.

(………………………….)

Paritosh Poudel

Class Roll no:14472/2014

vi

TABLE OF CONTENTS

RECOMMENDATION BY SUPERVISOR ......................................................................... ii

VIVA - VOCE SHEET ......................................................................................................... iii

STUDENTS DECLARATION............................................................................................. iv

ACKNOWLEDGEMENTS ................................................................................................... v

TABLE OF CONTENTS...................................................................................................... vi

LIST OF TABLES .............................................................................................................. viii

LIST OF FIGURES .............................................................................................................. ix

ABBREVIATION: ................................................................................................................ x

EXECUTIVE SUMMARY .................................................................................................. xi

CHAPTER I INTRODUCTION ........................................................................................... 1

1.1 Context information ..................................................................................................... 1

1.2 Statement of Problem ................................................................................................... 2

1.3 Purpose of the study: .................................................................................................... 2

1.4 Significance of the study .............................................................................................. 3

1.5 Literature survey .......................................................................................................... 4

1.5.1Review of related studies........................................................................................ 4

1.5.2 Concluding remarks............................................................................................... 9

1.6 Research methods......................................................................................................... 9

1.6.1 Research design ..................................................................................................... 9

1.6.2 Source of data ...................................................................................................... 10

1.6.3Data collection tools ............................................................................................. 10

1.6.4 Population and Sample ........................................................................................ 10

1.6.5 Data analysis tools ............................................................................................... 11

vii

1.7 Limitation of the Study .............................................................................................. 13

1.8 Organization of the study ........................................................................................... 14

CHAPTER II DATA PRESENTATION AND ANALYSIS .............................................. 15

2.1 Organizational profile ................................................................................................ 15

2.2 Data presentation and analysis ................................................................................... 18

2.2.1Analysis of Net profit margin (NPM): ................................................................. 18

2.2.2 Analysis of Return on Assts. ............................................................................... 20

2.2.3 Analysis of weighted average interest rate spread .............................................. 22

2.2.4 Aggregate analysis of NPM, ROA and IRS of all three selected banks.............. 24

2.2.5 Analysis of correlation and regression model: .................................................... 25

2.3 Major Findings and discussion .................................................................................. 27

CHAPTER III CONCLUSION AND ACTION IMPLICATION ....................................... 28

3.1 Summary of the Findings ........................................................................................... 29

3.2 Action implication ...................................................................................................... 29

REFERENCES

APPENDICES

viii

LIST OF TABLES

Table 1.1 Sample Banks and the Year of study ................................................................... 10

Table 2.1 List of all commercial banks in Nepal ................................................................ 16

Table 2.2 Profile of sample banks ....................................................................................... 18

Table2.3 Data and Descriptive statistics of NPM of NIB, SBI and GBIME ...................... 19

Table2.4 Data and Descriptive statistics of ROA of NIB, SBI and GBIME ...................... 21

Table2.5 Data and Descriptive statistics of NIB, SBI and GBIME .................................... 23

Table2.6 Aggregate analysis of NPM, ROA, and IRS ........................................................ 24

Table 2.7 Correlation analysis between W. Avg IRS and NPM ......................................... 25

Table 2.8 Regression analysis of W. Avg IRS and NPM .................................................... 25

Table2.9 Correlation between ROA and W. Avg IRS ......................................................... 26

Table 2.10 Regression analysis of ROA and W. Avg IRS .................................................. 26

ix

LIST OF FIGURES

Figure 1.1: Independent and Dependent variable ................................................................ 13

Figure 2.1 Trend Chart of NPM of sample banks……........................................................21

Figure 2.2 Trend chart of ROA of sample banks. ................................................................ 22

Figure 2.3 Trend Chart of IRS of Sample Banks ................................................................. 24

x

ABBREVIATIONS

BBA: Bachelor of Business Administration

C.V: Coefficient of variation

EPS: Earning Per Share

GBIME: Global IME Bank

IRS: Interest Rate Spread

NIB: Nepal Investment Bank

No. : Number

NPM: Net Profit Margin

ROA: Return on Assets

ROE: Return on Equity

SPSS: Statistical Package for Social Scientist

Wet Avg : Weighted Average

xi

EXECUTIVE SUMMARY

Interest income contributes the major portion of net profit of any depositary institution. The

volume of total lending, total deposits and mobilization of fund depends upon the interest

rate charged and offered by the bank. This study assesses the impact of interest rate spread

on profitability of commercials banks in Nepal. The purpose of the study was to assess the

level of impact of interest rate spread on profitability. Also, the purpose of this study was

to identify and analyze the change of interest rate spread over the period of nine years from

2065/66 to 2073/74 B.S. The independent variable was weighted average interest rate

spread and depended variables were return on assets and net profit margin. Descriptive

statistics and regression analysis were used for data analysis. Population size was 28

commercial banks of Nepal and sample size were 3 commercial banks of Nepal. The

finding showed positive relationship between interest rate spread and profitability of class

“A” banks in Nepal

1

CHAPTER I

INTRODUCTION

1.1 Context information

The difference between lending and deposit interest rate is known as interest rate spread

(IRS).It is an important determinants of the efficacy of the financial system in a country. In

another word, the ways of measuring interest rate spread (IRS) in the literature, such as the

difference between interest income received and interest paid by a bank as a ratio of total

assets or difference between the ratio of interest received and all interest bearing assets and

the ratio of interest paid and all interest earning liabilities (Mujeri &Sayara,2009).

No doubt, there are both theoretical and practical link exist between interest rate and the

financial structure of a firm. Interest rate is defined as a fee charged by a lender to a

borrower for the use of borrowed money, usually expressed as an annual percentage of the

principal. The interest rate depends upon the time value of money, inflation rate, credit risk

of the borrower, liquidity risk and many more. Interest are charged when people/household

and corporations borrow funds for varying purposes from commercial to personal and paid

when people lend to financial institutions through different deposit vehicles.

Brock and Rojas (2000) defines interest rate spread as margin between interest income and

interest expenses as a percentage of total earning assets. Interest rate spreads impacts

directly to the cost of the capital for the borrower as well as it directly impact on

profitability of financial institution. No doubt, higher interest spread rate increases the

profitability and vice-versa.

Commercial banks can increase their profit margins through higher lending rates and

lower deposit rates. Banks do not charge loan rates that are too low because the revenue

from the interest income will not be enough to cover the cost of deposits, general expenses

and the loss of revenue from non-performing loan portfolio. On the other hand, they cannot

charge too high loan rates because they will not be able to keep the banking relationship

with the borrowers with high lending rate. Thus, determination of the appropriate lending

2

rates usually becomes a major issue in banking industry. Moreover, the factors that

determine the level of commercial banks‟ lending rates are important concerns not only for

specific banks but also to policy makers, the banking industry and the public at large.

Financial performance analysis is the process of identifying the financial strength and

weakness of the firm. Quarden (2004) argued financial performance analysis helps in

short-term and long term forecasting and growth which can be identified with the help of

financial performance analysis. The analysis of financial performance is a process of

evaluating the relationship between the component parts of financial statement to obtain

better understanding of the firm‟s position and performance. Similarly, profitability

analysis is also the process of identifying and analyzing the position of net profit, return on

investment, earning per share, and return on equity e.t.c. Profitability analysis is a branch

of financial performance analysis.

1.2 Statement of Problem

Bank interest rate spread simply refers to difference between the bank earning interest rate

from the customer and interest rate that given to the depositor of the banks. Banking

business largely based on the deposit and lending function. It is most important to maintain

balance between deposit and loan for any bank. Loan is one of the major sources of income

of the commercial banks. They provides loan to its customer by charging the certain

interest which is ultimately large source of revenue. For providing loan to any customer

bank need a fund, generally depositors do not deposit their money in the banks without

considering the interest rate and image of the banks. So, this research tried to obtained

answer of the following question:

What is the impact of interest rate spread on profitability of the commercial banks?

What are the trends of interest rate in commercial banks?

What are the major impacts of change in interest rate spread in commercial banks?

1.3 Purpose of the study:

The primary objective of this study is to determine the impact of interest spread rate on

profitability of commercial banks on Nepal. Thus, this study aims to assess the nature of

3

impact of interest rate offered by banks on deposit and interest rate charged by bank on

loan on profitability. However, the specified objectives of the study are listed as follows:

To examine the impact of interest rate spread on profitability of commercial banks

in Nepal.

To investigate the levels and trends in interest rate spreads in commercial bank in

Nepal from period of nine years.

To assess the level of change caused due to change in interest rate spread of

commercial banks in Nepal.

1.4 Significance of the study

Interest income contributes major portion of net profit of any bank. Level of interest

income is determined by the level of interest spread rate. The significance of this study is

to identify, analyze and interpret portion of impact on profitability of the interest spread

rate of bank. Profitability of Bank can be measured though the study of variables like

Return on Equity(ROE), Return on Assets(ROA), Earning per share (EPS), Book value per

share, Net profit margin (NPM), and many more. With the help of this study, we can

analyze and interpret the impact of interest spread rate on these variables of profitability.

Interest spread rate also affect total lending and total deposits in an economy. So, bank

must manage appropriate interest spread rate. Higher deposit interest rate encourages

depositors to deposit money on bank but, side by side, high lending interest rate

discourages business organization and household to carry loan from bank as it increases

cost of capital to them. So, bank must maintain appropriate lending and deposit rate that

can attract both depositor and debtor. This study will also help bankers to analyze the past

impact of interest rate spread and its impact on profitability. Some of the other significance

of this study is highlighted below:

It will help to identify the level of impact of interest rate spread on profitability of

leading commercial bank of Nepal.

It will help bankers to carry out necessary steps to determine appropriate lending

and deposit rate.

It will help new researchers to learn more about the interest rate and profitability of

commercial banks in Nepal.

4

It will empower me with more knowledge related to interest spread rate and

profitability.

1.5 Literature survey

Some useful literatures related to interest rate spread and banks profitability has been

reviewed. The main purpose of reviewing these articles and journals is to gain an idea on

the research studies that have been conducted earlier in the chosen field and what remains

to be done. This provides a foundation for developing comprehensive theoretical

framework and model. The theories will help to develop ideas, compare findings and

attaining.

1.5.1Review of related studies

Angbazo ( 1997) examined the determinants of bank net interest margins for a sample of

US banks using annual data for 1989- 1993 in a country specific basis. The results for the

pooled sample suggested that the proxies for default risk, opportunity cost of non-interest

bearing reserves, leverage and management efficiency are all statistically significant and

positively related to bank interest margins. The ratio of liquid assets to total liabilities, a

proxy for low liquidity risk, was inversely related to the bank interest margins.

Chirwa and Mlachila (2002) found that interest rate spreads in Malawi increased

significantly after implementing financial liberalization reforms due partially to high

monopoly power within the industry coupled with the high incidence of interlocking

ownership and directorship in the Malawian banking system which effectively stifled

competition. Their study strongly concluded that high interest rate spreads in developing

countries will persist if financial sector reforms do not alter the structure within which

banks operate.

Khawaja and Din (2007) investigate the determinants of interest rate spreads in Pakistan

using panel data on 29 banks for the period 1998 to 2005. They use the industry variables

of concentration and deposit inelasticity and firm variables including market share,

liquidity, administrative costs, asset quality, and the macroeconomic variables of real

5

output, inflation, and real interest rates. They conclude that the inelasticity of deposit

supply is a major determinant of interest rate spread.

Beck and Hesse (2009) analyzed factors explaining interest rate spreads in Uganda and

compared with peer African countries for the period between 1999 and 2005. They used

panel data set of 1390 banks from 86 countries. To explain the high variation in interest

rate margins across countries, they used bank size, exchange rate depreciation, real T bill

rate, liquidity ratio, concentration, inflation, GDP growth, institution development and

overhead costs. They reported that that most of the bank specific as well as macroeconomic

factor are relevant in explaining high banking margins in Uganda. However, the foreign

banks and changes in market structure had no significant relation with interest rate spreads.

They concluded that size, high T bill rates and institutional deficiencies explained large

proportions of Ugandan interest margins.

Maudos and Solis (2009) analyzed the determinants of net interest income in Mexican

banking sector for the period between 1993 and 2005. Their sample constituted of 43

commercial banks with 289 annual observations of an unbalanced panel data. They

observed high interest margins for Mexico. They considered various explanatory factors to

explain the behavior of banking spreads. These included operating costs, volatility of

interest rates, implicit interest payments, quality of management, non interest income,

credit risk, degree of risk aversion, market risk, transaction size, liquidity, cost to gross

income, GDP growth and inflation rate. The reported results reflected that except for

liquidity all other variables were significantly related to interest rate spreads. They

concluded that the high Mexican spreads are mainly a function of average operating costs

and market power while non interest income, despite of increasing over the years

economic.

Afzal and Mirza (2010) have explored the determinants of interest rate spread in Pakistan

commercial banking sector in the post-transition period (2004-2009), using an exhaustive

set of macro and firm level to analyze their impact on intermediary efficiency. They

introduced two innovative variables: the default likelihood indicator and the proportion of

public sector deposit in total deposit. The results suggested that the intermediary efficiency

is affected by banks size, operational efficiencies, asset quality, liquidity , risk absorption

6

capacity, and gross domestic product(GDP) growth rate. They could not find evidence to

support the impact of interest rate volatility and financial development indicators on

banking spreads.

Kipngetich (2011) examined the effect on interest rates on the performance of commercial

banks in Kenya. The study used published incomes statement of commercial banks

between 2006 and 2010 to model the relationship between interest rates and financial

performance. The study concluded that in the short term, interest rates did not have a

significant effect on profitability of commercial banks. The study recommended the

application of diversification strategies to enhance performance of commercial banks.

Perez(2011) has examined the components of interest rate spreads in Belize using

accounting data and then seeks to identify the factors that affect interest rate spreads using

a panel dynamic least squares model. The study concludes that market share and adversely

classified loans are two main determinants of the spread. Based on these findings, the study

suggests policy recommendations to reduce information asymmetries and increase

competition in the Belizean financial sector.

Mangeli(2012) has conducted a research to find out relationship between interest rate

spread and financial performance of the commercial banks in Kenya. The study adopted a

descriptive research design on a sample of quoted commercial banks in Kenya. The study

used secondary data and quantitative technique in data analysis to the relationship between

the interest rate spread and performance of commercial banks. The findings of the research

concludes that interest rate spread affect the performance of commercial banks, as it

increases the cost of loans charged on the borrowers, regulations on interest rates have far

reaching effects on performance of commercial since they determine the interest rate

spread in banks and also help mitigate moral hazards incidental to performance of

commercial banks, credit risk management technique remotely affects the value of a bank‟s

interest rates spread as interest rates are benchmarked against the associated non-

performing loans and non-performing loans is attributable to high cost of loans.

Nazir, Butt and Nawaz (2012) worked on interest rate determinants of banks in Pakistan.

Data of 4 years of 30 banks was included in this research paper. Correlation analysis

7

techniques was used to find the relationship between weighted average rate of interest and

10 independent variables like bank specific factors, inflation rate, credit risk, amount of

deposit, administrative cost, profit margins, macroeconomic conditions etc. The results

showed that administrative costs, credit risk, deposit amounts and profit margins are

important factors to determine interest rate and they have positive relationship with interest

rate. The relation of Bank's liquidity and deposit amount is negative with interest rate.

While some factors have no significant relationship with interest rate like inflation rate and

market share.

Irungu(2013) has examined the effect of interest rate spread on financial performance of

commercial banks in Kenya. The target population in this study was 43 commercial banks

in Kenya and data were collected from central bank supervision report. SPSS (Statistical

Package for Social Scientists) and regression analysis were used to analyze the data and

find out whether exist a relationship between interest rate spread and performance of

commercial banks in Kenya. The study found that there is strong positive relationship

between financial performances of commercial banks with interest rate spread. Study found

variables are significance to influencing financial performance of Kenya banks. The study

found that interest rate spread affect performance assets in banks as it increases the cost of

loans charged on the borrowers, regulation on interest rates have far reaching effects on

assets non-performance. The study recommends there is need for government to regulate

interest rates as this would help to safeguard borrowers from exploitation by commercial

banks.

Okech (2013) undertook a study on the effect of lending rates on the performance of

commercial banks in Kenya. The study considered management efficiency and operating

cost efficiency, in regard to lending interest rate. The study found that a weak positive

relationship between lending rates and performance of commercial banks. Since interest

rates accounted for only 14.4% of the revenue in commercial banks, the study

recommended income source diversification for better performance.

Khan and Sattar (2014) studied “Impact of Interest Rate Changes on the Profitability of

four Major Commercial Banks in Pakistan”. In this research interest rate and bank

profitability were used as explanatory and explained variables respectively. Pearson

8

correlation model was used to conclude results. They concluded that a positive strong

relationship exist between interest rate and bank profitability

Mbao, Kapembwa, Mooka, Rasmussen and Sichalwe (2014) have studied the determinants

of bank lending rates in Zambia. They have employed panel regression techniques using

detailed bank-specific data. Their results indicate that lending rates are to a significant

extent influenced by variables relating to banks‟ costs. They found that inflation has

significant impact on nominal interest rates on an almost one-to-one basis. Apart from

inflation, however, elements of banks‟ balance sheet reveal that lending rates are to a

significant extent also positively impacted by variables associated with higher cost

structures or lower income.

Bhattarai( 2015) has investigated the determinants of lending rate of Nepalese commercial

banks. The analysis of data was based on a sample of 6 commercial banks observed over

the period 6 years (2010 to 2015). The models used in the study were: pooled OLS model,

fixed effects model and random effects model. This study has used „lending rate‟ as

dependent variable, while the explanatory variables are: operating cost to total assets ratio,

deposit interest rate, profitability (ROA) and default risk. The estimated results of these

three regression models reveal that operating costs to total assets ratio, profitability (ROA)

and default risk have significant positive impact on the commercial bank lending rate.

However, deposit rate has negligible impact on lending interest rate. Thus, this study

concludes that the major determinants of commercial banks‟ lending rate are: operating

costs to total assets ratio, profitability (ROA) and default risk in Nepalese perspectives.

Maina (2015) studied determinants of interest rate spread among commercial banks of

Kenya. This study adopted descriptive and correlation designs to determine relationship

between the independent variables and the interest rate spreads the dependent variable. The

sample units for this study were twenty seven (27) commercial banks. He concluded that

inflation, operating costs generally has no effects on interest rate spread among commercial

banks in Kenya while market structure, ownership structure and business risk play

important role in determination of interest rate spread.

9

Mwangi and Wambari (2017) studied the effect of interest rates on financial performance

of commercial banks in Kenya. The study adopted an explanatory research design.

Multiple linear regression models were used to analyze the data using statistical package

for social the social science (SPSS). The study concluded that there is a positive significant

relationship between lending rate ratio and financial performance of commercial banks.

The study also arrived at the conclusion that deposit interest ratio negatively affects bank

performance. Moreover, the study concluded that liquidity management and asset quality

affect performance positively and negatively respectively.

1.5.2 Concluding remarks

Based on the theory and past empirical studies, we came to know that interest rate spread

directly affect the profitability of the commercial bank. Interest rate spread is the difference

between lending rate and deposit rate. Although, there are various theories and past

research paper in the field of interest rate and profitability of commercial banks , there is

still lack of latest research and article, so this research will help to cover research gap to

some extent. This research is based on latest data available in annual report. So, this

research will guide the upcoming researcher for completing others similar research work.

1.6 Research methods

This study is based on the descriptive research design that uses secondary data. Descriptive

statistics are used to describe the basic features of the data in a study. They provide simple

summaries about the sample and the measures. Together with simple graphics analysis,

they form the basis of virtually every quantitative analysis of data.

1.6.1 Research design

A research design is simply the framework or plan for a study used as a guide in collecting

and analyzing data. Research designs can be classified into some basic types according to

fundamental objective of the research which include descriptive and exploratory. This

study is descriptive in nature.

10

1.6.2 Source of data

While doing study and preparing this report, the secondary source of data collection was

used. Secondary source of data collection includes those data which are obtained from the

published sources like newspaper, articles, books, companies‟ websites, magazines, and

many more. This study has mainly used audited annual published by the organization.

1.6.3Data collection tools

The quantitative data were used to prepare the project report which is assessed from the

annual reports published by the companies. The data were collected from the websites of

the respective companies.

1.6.4 Population and Sample

A small portion chosen from the population for studying its properties is called a sample

and the number of unit in the sample is known as the sample size. Since the research topic

is about the interest rate spread of commercial banks of Nepal, so, all the depository

institution of class A banks of Nepal are the member of population study.

The population for the study comprises 28 commercial banks. Out of the total commercial

banks operating in Nepal, 3 commercial banks are taken as the sample of the study from

the fiscal year 2065/66 to2073/74. Nepal Investment Bank Limited, SBI Bank Limited and

Global IME Bank Limited are taken as a sample.

Table 1.1

Sample Banks and the Year of study

SN Bank Fiscal year No. of period

observed

1 NIB 2065/66-2073/74 9

2 SBI 2065/66-2073/74 9

3 GBIME 2065/66-2073/74 9

TOTAL 27

11

1.6.5 Data analysis tools

1.6.5.1 Arithmetic Mean

Arithmetic mean is the sum of observation divided by the number of observation. In

such case all the items are equally important. It is referred some time as average simply

the mean.

Mean = ∑𝑿

𝒏

Where, X= Mean

∑X= Sum of all the variable X

n= variable involved

1.6.5.2 Standard deviation

The standard deviation is the best tools to measure fluctuation in any data. It is usually

denoted by sigma. The standard deviation is defined as the positive square root of the

arithmetic mean of the square deviations from their arithmetic mean of a set of values.

(𝝈) = ∑(𝑿 − 𝑿 )/𝒏

1.6.5.3 Correlation coefficient

Correlation coefficient is the statistical tools which measures the degree of relationship

of one variable with other variable. Two or more variables are said to be correlated if

change in the value of one variable appears to be related or linked with the change in

the other variables. Correlation may be positive or negative and ranges from -1 to +1,

there is positive perfect correlation; when r = -1. There is perfect negative correlation;

when r = 0. There is no correlation and when r = 0.5 then there is low degree of

correlation.

Simple correlation coefficient (r)

=𝑛∑𝑥1𝑥2 − ∑𝑥1𝑥2

𝑛∑𝑥12 − 𝑥1 2 𝑛∑𝑥22 − (𝑥2)2

12

1.6.5.4 Kurtosis

Kurtosis is statistical measure that is used to describe the distribution, of observed data

around the mean sometimes referred to as the volatility of volatility. Kurtosis is used in

statistical field to describe in the trend charts. Kurtosis can be present in a chart with fat

tails and a low, even distribution, as well as be present in a chart with skinny tails and

distribution concentrated toward mean.

K =

1

2( 𝑄3−𝑄1)

𝑃90−𝑃10

Where,

Q= quartile

P= percentile

Interpretation style of calculated value

If K = 0.263, the distribution is meso kurtic or normal

If K< 0.263, the distribution is lepto kurtic

If k< 0.263, the distribution is platy kurtic

1.6.5.5 Skewness

Skewness is asymmetry in a statistical distribution, in which the curve appears distorted or

skewed either to the left or to the right. Skewness can be quantified and define the extent to

which a distribution differs from normal distribution.

Sk(P) = 3(𝑀𝑒𝑎𝑛 −𝑀𝑒𝑑𝑖𝑎𝑛 )

𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛

Interpretation of calculated value of coefficient of skewness

If Sk(P) = 0, then this shows that the distribution is symmetrical (non -skewed)

If Sk(P) > 0, then this shows that the distribution is positively skewed or right

skewed

If Sk(P) <0, then this shows that the distribution is negatively skewed or left skewed

13

1.6.5.6 Study variables

Independent Variable Dependent Variable

Figure 1.1: Independent and Dependent variable

In this study, weighted average interest rate spread is taken as independent variables

whereas return on assets and net profit margin is considered as dependent variables. The

study focuses to examine the impact of weighted average interest rate spread on return on

assets and net profit margin.

1.7 Limitation of the Study

Although this research uses latest data available, there are some limitations of the study.

Some of the limitations of this research work are listed below:

Out of 28 commercial banks currently operating, only 3 leading commercial banks

are undertaken under the study. The sample has been drawn at random for

convenience and for easy availability of data. So there may exist some sampling

error.

This study only covers nine fiscal year.

The study is based on secondary data. There is no use of primary data. So the

reliability of study depends upon the reliability of published data of the respective

commercial banks.

Stipulated time and resources are also limitation of the study as the main objective

is to fulfill the partial requirement of bachelor in business administration.

This research is mainly done to fulfill the partial requirement of Bachelor of

Business Administration of Tribhuvan University, so limited time and resources are

also the main limitation of the study.

Weighted average

interest rate spread

ROA, NPM

14

Lack of research experiences and lack of enough study materials are the other

limitation of this study.

The study has only used the data of Commercial banks, it has not considered the data of

other depository institutions like development bank, finance company, saving and credit

cooperatives, micro finance e.t.c.

1.8 Organization of the study

This project report is prepared for the partial fulfillment of the requirements for the degree

of Bachelor of Business Administration. In this report whole chapter is classified into the

three parts.

Chapter I: Introduction section includes Background of the study, statement of the

problem, objective of the study, significance of the study, literature review, Research

Methodology, limitation of the study and Organization of the study

Chapter II: Data presentation and analysis section includes organization profile, Data

analysis and major finding of the study.

Chapter III: Conclusion and Action Implications.

15

CHAPTER II

DATA PRESENTATION AND ANALYSIS

2.1 Organizational profile

Bank is a depositary financial institution that collects deposit from the surplus unit of an

economy and lends loan to deficit unit of an economy. It is highly regulated business all

over the world. In another word, bank can be defined as any business organization that

offers acceptance of deposits, which is subject to withdrawal on demand (either through

check or electronic transfer, or both) and grants loans and credit to private individual and

business firms on commercial basis.

Banking sector of Nepal has got massive growth and potential over the years. There is a

considerable expansion in the profitability of banking sector. Banking sector of Nepal,

sometimes face problems like liquidity, and solvency which have considerable impact on

the performance of banking sector and financial system. The situation and problem of

liquidity and solvency can be resolved by managing enough amount of liquidity. Banks

operate in very competitive and complex environment. It has become obligatory to pay

handsome interest to attract the liquidity. On the other hand, increased knowledge about

the share market to general public is also leading the liquidity problem in the banking

sectors since the attractive return, despite the risk is attracting the people who have money

in their hands. To make banking system stable requires stable macroeconomic environment

which adds to efficient and effective growth of savings and investment decision. The

performance of banking system particularly in the areas of monetary policy, transparent

fiscal policy and financial stabilization should be supported by macroeconomic measures.

Nepal Rastra Bank plays an important role in the efficient and effective growth of economy

by providing guidelines to the financial institutions thus facilitating the investors and

mobilizing the resources of the economy for development in the country. The cheapest

source of funding for competitive banking institution is profit and it is a major requirement

for banking sectors. The rising competition in the financial market makes it necessary for

the success of banking industry. These key facts are the reason to focus in the present issue

of bank profitability.

16

As we know bank provide financial service to the customers and a reward bank charge

interest. Most funds are collected through depositors and they also receive interest. Interest

is the margin between the bank earning on its assets and payment to depositors. Interest is

the rent paid for the use of money. The interest rate is determined by the demand and

supply of the loanable fund. Interest rate plays a very important role in allocation of

resources in the decision making of consumer and business. For example, based on

monetary policy if NRB changes interest rate then the changes in the interest rate will

influence the cost of capital and as a result the investment decision and level of

consumption will be affected. When the interest rate of depositors decrease and due to that

if spread increases then it will discourage the savings and on the other hand, if interest rate

to depositor increases then it will badly affect the investment. That is why there are

important implications of these changes in the interest rate on the economy. As compared

to other institutions banks are more sensitive to the change in the interest rates. The fee

paid for using someone else money is generally known as interest. Interest rate sends price

signals to borrowers, lenders and savers. Higher interest rate generally brings a high

amount of saving which simultaneously increase the investment. Lower rate of return on

the other hand tend to reduce the volume of borrowing and capital investment. Usually

interest rate is expressed in annual percentage

Currently there are 28 commercials banks operating in Nepal. The lists of commercial

banks are given below:

Table 2.1

List of all commercial banks in Nepal

S.N. Name of commercial Banks Established year (A.D)

1 Laxmi Bank Limited 2002

2 Siddhartha Bank Limited 2002

3 Nepal Bank Limited 1937

4 Rstriya Banijya Bank Limited 1966

5 Agriculture development Bank 2006

6 Nabil Bank Limited 1984

17

7 Nepal investment Bank Limited 1986

8 Standard chartered bank Nepal Limited 1987

19 Himalayan Bank limited 1993

10 Nepal SBI Bank Limited 1993

11 Nepal Bangladesh Bank limited 1993

12 Everest Bank Limited 1994

13 Kumari Bank Limited 2001

14 Bank of Kathmandu Limited 1995

15 Nepal credit and commerce Bank limited 1996

16 Global ime Bank Limited 2007

17 Citizens Bank international limited 2007

18 Prime commercial Bank Limited 2007

19 Sunrise Bank Limited 2007

20 NMB Bank Limited 2008

21 NIC Asia Bank Limited 1998

22 Machhapuchhre Bank Limited 2000

23 Mega Bank Nepal Limited 2010

24 Civil Bank Limited 2010

25 Century Bank Limited 2011

26 Sanima Bank limited 2012

27 Janta Bank Limited 2010

28 Prabhu Bank limited 2016

Source: www.nrb.org.np

18

A short description of sample bank can be obtained from following table.

Table 2.2

Profile of sample banks

Bank Established Year No. of staffs Number of ATM. Number of Branches

NIB 1986 1187 98 61

SBI 1993 768 62 96

GBIME 2007 1348 128 120

All the sample banks are the leading commercial banks in Nepal. Among them, NIB is the

oldest bank where as GBIME is the youngest bank. As per the number of branches and

ATM machines, GBIME comes at first position.

2.2 Data presentation and analysis

The data related to interest rate spread and profitability of concerned bank is collected

form annual report published by the bank from its key principle indicator section. In this

data presentation and analysis section, collected data are presented and its analysis id done.

For the analysis of interest rate spread, weighted average interest rate is taken and for the

analysis of profitability, variables like return on assets (ROA), net profit margin (NPM) is

taken. Analysis is carried out by using simple regression model and descriptive statistics

tools.

2.2.1Analysis of Net profit margin (NPM):

Net profit margin (NPM) represents the ratio of net profits to total revenue of the business.

It reflects effectiveness of expenses of expense management, cost control, and service

pricing policies of the banks. Typically expressed as a percentage, net profit margins show

how much of each amount collected by a company as revenue translates into profit. Table

2.1.1 shows the position of NPM with respect to the Nepal Investment Bank (NIB), SBI

bank and Global IME bank (GBIME).

19

Table2.3

Data and Descriptive statistics of Net profit margin of NIB, SBI and GBIME

Fiscal Year NPM of NIB NPM of SBI NPM of GBIME

2065/066 24 19.14 7.87

2066/067 23.9 15.36 10.92

2067/068 18.2 13.21 26.19

2068/069 15.5 11.25 28.97

2069/070 28.3 16.47 24.4

2070/071 27.8 19.97 41.05

2071/072 28.1 23.22 30.32

2072/073 31 27.17 35.03

2073/074 28.1 21.55 42.34

Mean 24.99 18.59 27.45

Standard deviation 5.16 5.05 11.95

C.V 0.21 0.26 0.44

Minimum 15.5 11.25 7.87

Maximum 31 27.17 42.34

Skewness -0.98 0.20 -0.55

Kurtosis -0.06 -0.51 -0.52

As per the table 2.3, NPM of GBIME seems strong. The mean value of GBIME‟s NPM

(27.45%) is greater than that of SBI (18.59%) and NIB (24.99%). The value of maximum

NPM also shows strong status of GBIME then that of SBI and NIB. Comparatively, status

of NIB also seems good with respect to minimum and maximum NPM than SBI. The

standard deviation (S.D) of NPM data over nine years shows much higher (S.D=11.95) of

GBIME than of SBI (S.D=5.05) and NIB (S.D=5.16). It indicates much volatility and high

earning risk with respect to the NIB and SBI in absolute basis. Since standard deviation

measures absolute risk, coefficient of variation (CV) has also been calculated to analyze

the relative earning risk. Accordingly, the result shows the earning risk of NIB is lower

than SBI and GBIME.

Recognizing the role of the nature and shape of data distribution in further statistical

analysis, the skewness and kurtosis of NPM has been measured as a part of descriptive

20

statistics. Skewness reflects the asymmetry of a distribution. The NPM of NIB and GBIME

are negatively skewed where the NPM data of SBI is positively skewed. A distribution

with a negative kurtosis value indicates that the distribution has lighter tails and a flatter

peak than the normal distribution. NPM data of both the banks indicates such a situation.

The overview of the aforesaid analysis is illustrated in the trend chart. Figure 2.1 gives the

glimpse of the trend of net profit margin (NPM) of Nepal Investment Bank, Nepal SBI

Bank Ltd and Global IME Bank Ltd.

Figure 2.1 Trend Chart of NPM of sample banks.

2.2.2 Analysis of Return on Assts.

Return on assets (ROA) is an indicator of how profitable a company is relative to its total

assets. ROA gives an idea as to how efficient management is at using its assets to generate

earnings. It is calculated by dividing a company's annual earnings by its total assets, ROA

is displayed as a percentage. Table 2.4 shows the position of ROA with respect to the

Nepal Investment Bank (NIB), SBI bank and Global IME bank (GBIME).

0

5

10

15

20

25

30

35

40

45

NP

M

Year

Trend Chart of NPM of Sample Banks

NPM NIBL

NPM SBI

NPM GBIME

21

Table2.4

Data and Descriptive statistics of Return on Assets of NIB, SBI and GBIME

Fiscal Year ROA of NIB ROA of SBI ROA of GBIME

2065/066 1.7 1.05 0.21

2066/067 2.2 1.03 0.42

2067/068 2 1.01 1.28

2068/069 1.6 0.83 0.87

2069/070 2.6 1.19 1.15

2070/071 2.3 1.5 1.62

2071/072 1.9 1.7 1.39

2072/073 2 2 1.58

2073/074 2.1 1.68 1.72

Mean 2.09 1.37 1.25

Standard deviation 0.29 0.41 0.44

C.V 0.14 0.30 0.35

Minimum 1.6 0.83 0.42

Maximum 2.6 2 1.72

Skewness 0.16 0.21 -1.03

Kurtosis 0.95 -1.38 0.62

As per the table 2.4, ROA of NIB seems strong. The mean value of ROA of NIB (2.09) is

much greater than of SBI (1.37) and GBIME (1.25). The value of minimum and maximum

also shows the strong status of NIB in comparison with SBI and GBIME. Also, the

standard deviation of NIB regarding ROA is less than standard deviation of other two

banks. It indicates less volatility and low return risk with respect to SBI and GBIME in

absolute basis. The ROA data of GBIME is negatively skewed where as ROA data of NIB

and SBI are positively skewed. The coefficient skewness regarding ROA data of NIB and

SBI seems fairly symmetrical. It is because the coefficient is in the range of -0.5 and 0.5.

22

The overview of the aforesaid analysis is illustrated in the trend chart. Figure 2.1 gives the

glimpse of the trend of net profit margin (NPM) of Nepal Investment Bank, Nepal SBI

Bank Ltd and Global IME Bank Ltd.

Figure 2.2 Trend chart of ROA of sample banks.

2.2.3 Analysis of weighted average interest rate spread

The weighted average interest rate is the difference between aggregate rate of interest

charged to loan and aggregate rate of interest paid to depositors. Accepting deposits and

granting credit is the primary function of depository institution so, interest rate plays a

major role in determining the volume of transaction on these primary functions. Table

2.5shows the percentage of average weighted interest rate of Nepal Investment Bank, SBI

Bank, and Global IME Bank.

0

0.5

1

1.5

2

2.5

3

RO

A

Year

Trend Chart of ROA of Sample Banks

ROA NIBL

ROA SBI

ROA of GBIME

23

Table2.5

Data and Descriptive statistics weighted average interest rate spread of NIB, SBI and

GBIME

Fiscal Year IRS of NIB IRS of SBI IRS of GBIME

2065/066 3.9 2.84 3.05

2066/067 4.4 2.76 3.05

2067/068 4.1 2.86 3.27

2068/069 4.5 2.7 3.88

2069/070 5.5 3.38 4.21

2070/071 4.8 3.45 5.34

2071/072 4.6 3.85 4.11

2072/073 4.7 4.00 4.52

2073/074 4.3 3.68 3.36

Mean 4.53 3.28 3.87

Standard deviation 0.46 0.52 0.77

C.V 0.02 0.16 0.20

Minimum 3.9 2.7 3.05

Maximum 5.5 4 5.34

Skewness 0.95 0.17 0.75

Kurtosis 1.83 -1.81 0.05

As per the table 2.5, the weighted average interest rate spread of NIB seems higher than

SBI and GBIME. The mean value of average weighted average interest rate spread over

nine years (4.53%) is more than that of SBI (3.28%) and GBIME (3.87). The value of

minimum and maximum interest rate spread also shows same. It means the difference

between lending rate and deposit rate if NIB id higher than other two sample banks.

However, standard deviation of interest rate spread of GBIME is higher (0.77) than that of

SBI (0.52) and NIB (0.46). It indicates more volatility and risk of GBIME with respect to

NIB and GBIME. All the data of interest rate spread of sample banks are positively

skewed.

24

The overview of the aforesaid analysis is illustrated in the trend chart. Figure 2.3 gives the

glimpse of the trend of IRS of Nepal Investment Bank, Nepal SBI Bank Ltd and Global

IME Bank Ltd.

Figure 2.3 Trend Chart of IRS of Sample Banks

2.2.4 Aggregate analysis of NPM, ROA and IRS of all three selected banks.

Table2.6

Aggregate analysis of NPM, ROA, and IRS

Variables Mean S.D C.V Minimum Maximum Skewness Kurtosis

NPM 23.68 8.63 0.36 7.87 42.34 0.23 -0.1

ROA 1.5 0.57 0.38 0.21 2.6 -0.36 -0.07

IRS 3.89 0.77 0.20 2.7 5.5 0.21 -0.63

Table 2.6 reflects the overall profitability in a single table. It has included aggregate NPM,

ROA, and IRS of all selected commercial banks. The average (mean) NPM of is 23.68%

where as ROA of sampled bank in aggregate form is 1.5%. Similarly, the minimum NPM

over the period of nine years is 7.87 where as maximum NPM is 42.34 %. The average

interest rate spread of all sample banks is 3.89%. It indicates that there is difference of

3.89% between lending interest rate and deposit interest rate in aggregate of all sample

banks. The minimum IRS of sample banks is observed 2.7% where as maximum IRS is

observed 5.5%. The C.V of ROA is higher than C.V of NPM and ROA. A coefficient of

variation (CV) is a statistical measure of the dispersion of data points in a data series

0

1

2

3

4

5

6

W.A

vg.I

RS

Year

W.Avg.IRS OF NIBL

W.Avg.IRS of SBI

W.Avg.IRS GBIME

25

around the mean. The coefficient of variation represents the ratio of the standard

deviation to the mean, and it is a useful statistic for comparing the degree of variation from

one data series to another, even if the means are drastically different from one another.

Therefore, the variation in ROA is high and variation in ISR is low.

Similarly, the aggregate data of ROA is negatively skewed where as NPM and IRS is

positively skewed. Recognizing the role of the nature and shape of data distribution in

further statistical analysis, the skewness and kurtosis of NPM has been measured as a part

of descriptive statistics. Skewness reflects the asymmetry of a distribution. A distribution

with a negative kurtosis value indicates that the distribution has lighter tails and a flatter

peak than the normal distribution. NPM, ROA and IRS of all banks in aggregate form

indicate such a situation.

2.2.5 Analysis of correlation and regression model:

Correlation shows the relationship between the variable. In this section relation between

the net profit margin, return on asset and weighted average interest rate spread is shown.

Table 2.7

Correlation analysis between weighted average interest rate spread and NPM

Wet.Avg. IRS (%) NPM(%)

Wet.Avg. IRS (%) 1

NPM(%) 0.63 1

Table 2.7 shows relationship between the weighted average interest rate spread and net

profit margin. Here the correlation of weighted average interest spread rate and net profit

margin is 0.63 which indicate positive relation between these two variables. If the weighted

average interest rate is increase, the NPM also increase in the positive manner.

Table 2.8

Regression analysis of weighted average interest rate spread and NPM

Intercept R-square R adjusted p-value Frequency Significance

-3.5312 0.3918 0.36748 0.6137 16.1052 4.79E-04

26

The table 2.8 presents the overall regression coefficient of observed variables. The

statistics in table shows that, there is a perfect model fit with an F-statistics of 16.1052,

significance at 95%. This means that the model specification is correct and that the selected

independent variable is determinants of NPM. Here significance is less than 0.05 which

indicates the model is fit and there is relationship between the dependent and independent

variables. The model summary also shows that R is 0.63 with p-value 0.6 imply that there

is very significant relationship between the weighted average spread rate and NPM. It also

shows that model explain up to 39.18% of the variation in the NPM of the banks. Adjusted

NPM is account for taking all observation, so, this show variation is 36.75%.

Table2.9

Correlation between ROA and weighted average interest rate spread

Wet.Avg. IRS (%) ROA(%)

Wet.Avg. IRS (%) 1

ROA(%) 0.746786 1

Table 2.9 shows relationship between the weighted average interest rate spread and return

on assets. Here the correlation of weighted average interest spread rate and return on assets

is 0.75 which indicate positive relation between these two variables. If the weighted

average interest rate is increase, the ROA also increase in the positive manner.

Table 2.10

Regression analysis of ROA and weighted average interest rate spread

Intercept R-square R adjusted p-value Frequency Significance

-0.6366 0.55769 0.27703 0.11391 31.5213 7.67E-06

The table 2.10 presents the overall regression coefficient of observed variables. The

statistics in table shows that, there is a perfect model fit with an F-statistics of 31.5213,

significance at 95%. This means that the model specification is correct and that the selected

independent variable is determinants of ROA. Here significance is less than 0.05 which

indicates the model is fit and there is relationship between the dependent and independent

variables. The model summary also shows that R is 0.75 with p-value 0.12; imply that

there is very significant relationship between the weighted average spread rate and ROA. It

27

also shows that model explain up to 27.70% of the variation in the ROA of the banks.

Adjusted ROA is account for taking all observation, so, this show variation is 27.70%.

2.3 Major Findings and discussion

A bank is a depositary institution. Its primary function is to accept deposit and grants loan

for household and business sector. It transfers funds from surplus unit of an economy to

deficit unit of an economy.

Interest income is the main income of any depository institution. Bank charge interest to

the lender and provide interest to the depositors. The difference between interest charged

and paid is simply known as interest rate spread. The study shows that there is positive

relationship between interest rate spread and profitability of commercial banks in Nepal.

The major findings of the study after the analysis of secondary data are as follows:

The average NPM of all sample banks is 23.68% and ROA is 1.5% and IRS is

3.89% over the observed period of 9 years from 2065/66 to 2073/74.

The average NPM of GBIME seems stronger than NIB and SBI but average ROA

of NIB is stronger than SBI and GBIME.

The weighted average interest rate spread of NIB is greater (4.53%) than SBI and

GBIME over the observed period.

There is positive relationship between weighted average IRS, ROA and NPM.

The correlation between IRS and ROA is 0.74% whereas correlation between NPM

and IRS is 0.63 %.

It indicates if ISR increases then it results to the increase in NPM and ROA.

28

CHAPTER III

CONCLUSION AND ACTION IMPLICATION

Bank is a depositary institution which collects fund from surplus unit of an economy and

grants loan to the deficit unit of an economy. Bank charges interest on lending and provide

interest on deposit. The difference between lending interest rate and deposit interest rate in

known as interest rate spread. Interest income is the major income of any depositary

institutions. This study focus on the impact of interest rate spread on income of commercial

banks in Nepal.

This study is based on secondary data. All the data were collected from the annual report

of respective banks from the section of key principle indicator. The study is descriptive in

nature. The ROA, NPM is taken as a variable to measure profitability and weighted

average interest rate spread is considered as a variable of interest rate spread.

By studying the weighted average interest rate of all samples banks, the minimum IRS was

2.7% and maximum was 5.5%. This indicates that interest rate is changing over time. The

study shows that where there is high interest rate spread, there will be high profitability i.e

high return on equity, high net profit margin e.t.c.

The findings of this research are not only being an academic contribution but also useful to

the policymakers in taking further measures to ensure efficient and competitive banking

sector of Nepal. It may be suggested that the policy makers / regulators should look into

the key determinants influencing the IRS and guide the commercial banks to maintain the

stable IRS through appropriate measures.

29

3.1 Summary of the Findings

Interest rate directly impact on overall economic activity of a nation. Low interest rate to

borrower encourages them to take loan from bank whereas low interest rate to depositors

discourages them to deposit money on the bank. So bank has to make balance between

deposit rate and lending rate. A bank should maintain optimum level of interest rate spread

to attract both depositors and debtor.

The study concluded that there is clear positive relationship between interest rate spread

and banks profitability. When interest rate spread increases, it will lead to increase

profitability, i.e. increase in return on equity, return on assets, net profit margin, earning

per share e.t.c. and vice versa.

3.2 Action implication

The study has explored the impact of interest rate spread on profitability of commercial

banks in Nepal. The impact of IRS in different variables of profitability has been observed.

The research is conducted by using latest data. This research gave clear evidence that

factor of profitability is directly affected by interest rate spread. Te study has checked the

level of impact of change in profitability by change in spread rate by using correlation and

regression model. On the basis of analysis and findings of study, following action

implication can be pointed out:

Interest rate is very sensitive factor for a banking industry, so bank must determine

an interest rate in competitive way.

Bank should determine an interest rate in such a way that it could attract both

depositor and debtor.

This research is conducted based on latest data including last fiscal year, so it is a

real picture of commercial banks.

The new researcher can use it as a reference for conducting study on similar topic.

30

Reference

Angbazo, L. (1997) Commercial bank net interest margins, default risk, interest rate risk

and off-balance sheet banking. Journal of Banking and Finance, 21, 55–87.

Beck, T. and Hesse, H., (2009).Why are interests spreads so high in Uganda? Journal of

Development Economics, 88, 192 –204.

Bhattarai, Y. R. (2015). Determinants of Lending Interest Rates of Nepalese Commercial

Banks, Economic Journal of Development Issues 19 & 20 (1-2.)

Brock, P. and Rojas-Suárez, L. (2000) Understanding the Behaviour of Bank Spreads in

Latin America, Journal of Development Economics, 71(2), 291-299.

Chirwa, Ephraim and Montfort Mlachila, Financial Reforms and Interest Rate Spreads in

the Commercial Banking System in Malawi,” IMF Working Paper No. wp/02/06,

2002.

Irungu, P.N. (2013). The effect of interest rate spread on financial performance of

commercial banks in Kenya (Unpublished Master‟s Thesis). University of Nairobi,

Kenya

Kipngetich, K. M. (2011). The relationship between interest rates and financial

performance of commercial banks in Kenya (Unpublished Masters Thesis).

University of Nairobi, Kenya.

Khan, W. A., & Sattar, A. (2014). Impact of Interest Rate Changes on the Profitability of

four Major Commercial Banks in Pakistan. International Journal of Accounting

and Financial Reporting, 4(1), 142.

Khawaja, M. I., & Din, M. U. (2007). Determinants of interest spread in Pakistan. The

Pakistan Development Review, 129-143.

Michalel, M.Y. (2012), Relationship between interest rate spread and financial

performance of the commercial banks in Kenya. University of Nairobi, Kenya

Maudos, J. & Solis, L., (2009).The determinants of net interest income in the Mexican

banking system: An integrated model. Journal of Banking and Finance

Mbao, F.Z., Kapembwa, C., Mooka, O., Rasmussen, T., & Sichalwe, J.

(2014).Determinants of bank lending rates in Zambia: A balance sheet approach.

Working Paper, WP/02.

Mirza, N & Afzak, A.(2010) The Determinants of Interest Rate Spread in Pakistan’s

Commercial Banking Sector. CREB working paper no.01-10, centre for research in

economics and business, Lahore school of economics.

Mujeri, M. K. & Sayera Y. 2009. An Analysis of Interest Rate Spread in the Banking

Sector in Bangladesh. The Bangladesh Development Studies, 32(4),1-33.

Maina, M. W. (2015). Determinants of interest rate spread among commercial banks of

Kenya (Doctoral dissertation). University of Nairobi, Kenya

Nazir, M. S., Butt, A., & Nawaz, M. M. (2012). Interest rate determinants of banks in

Pakistan. Актуальні проблеми економіки, (3), 415-424.

Okech,F.O.(2013). The Effect of Lending Interest Rates on Financial Performance of

Commercial Banks in Kenya (Unpublished Master‟s Thesis). University of Nairobi,

Kenya

Perez, P.(2011) Determinants of Interest Rate Spread in Beliz. Research Department,

Central Bank of Belize

Quaden, G. (2004). Efficiency and stability in an evolving financial system. National Bank

of Belgium Conference on Efficiency and Stability in an Evolving Financial System,

Brussels, Belgium. Retrieved from http://www.bis.org/review/r040521b.pdf.

Wambari, D.K. & Mwangi, M. (2017), Effect of Interest Rates on the financial

performance of commercial banks in Kenya. International Journal of Finance and

Accounting, 2(4),19- 35.

APPENDICES

Bank Year ROA(%) NPM W.Avg. IRS (%)

NIBL 2065/66 1.7 24 3.9

NIBL 2066/67 2.2 23.9 4.4

NIBL 2067/68 2 18.2 4.1

NIBL 2068/69 1.6 15.5 4.5

NIBL 2069/70 2.6 28.3 5.5

NIBL 2070/71 2.3 27.8 4.8

NIBL 2071/72 1.9 28.1 4.6

NIBL 2072/73 2 31 4.7

NIBL 2073/74 2.1 28.1 4.3

SBI 2065/66 1.05 19.14 2.84

SBI 2066/67 1.03 15.36 2.76

SBI 2067/68 1.01 13.21 2.86

SBI 2068/69 0.83 11.25 2.7

SBI 2069/70 1.19 16.47 3.38

SBI 2070/71 1.5 19.97 3.45

SBI 2071/72 1.7 23.22 3.85

SBI 2072/73 2 27.17 4.00

SBI 2073/74 1.68 21.55 3.68

GBIME 2065/66 0.21 7.87 3.05

GBIME 2066/67 0.42 10.92 3.05

GBIME 2067/68 1.28 26.19 3.27

GBIME 2068/69 0.87 28.97 3.88

GBIME 2069/70 1.15 24.4 4.21

GBIME 2070/71 1.62 41.05 5.34

GBIME 2071/72 1.39 30.32 4.11

GBIME 2072/73 1.58 35.03 4.52

GBIME 2073/74 1.72 42.34 3.36

Source: Annual Report 2065/66 to 2073/74