credit process workshop day two - abj.org.jo process wor… · credit scoring methodology...

Credit Process Workshop

April 2008

Day Two

Agenda

9:00 – 11:00

� Credit Scoring

11:00 – 11:15 AM

Break

11:15 – 1:00 PM

Integrated Rating System Design

1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM

Credit Risk Infrastructure and Risk Rating Automation

3:00 – 3:15 PM

Break

3:15 – 4:00 PM

Recap and Q & A

9:00 – 9:30 AM

Introduction, Welcome and Review of Objectives

9:30 – 11:00 AM

Credit Process: Challenges and Leading Practices

11:00 – 11:15 AM

Break

11:15 – 1:00 PM

Technology/Data Considerations and Challenges

1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM

Sample Solution and Demo

3:00 – 3:15 PM

Break

3:15 – 4:00 PM

Case for Change and Program Approach

Day 2Day 1

Credit Process WorkshopDay Two

• Norwin Estrada - is a Manager in the Financial Services practice of BearingPoint based in New York City. He is a skilled consultant with significant experience leading a wide range of assignments covering commercial credit, risk management, business requirements analysis, and regulatory and compliance based initiatives. Mr. Estrada specializes in credit processes and customer management, along with operational efficiency and control. Norwin has extensive hands-on experience with all types of business lending products and credit qualities. He has also participated in the development of commercial lending solutions within BearingPoint’s North American practice. [email protected] cell phone: +1-917-907-2635

• Kevin O’Brien - is a Manager in the Emerging Markets practice of BearingPoint with deep experience in trade financing, commercial banking and financial consulting. He holds an Undergraduate Degree in Business from the State University of New York; a Masters in Business from American University in Washington DC; and a Jurist Doctorate from George Mason University School of Law in Virginia where he served as Adjunct Professor. Mr. O’Brien is a member of the Virginia and District of Columbia Bar Associations. As a banker, Mr. O’Brien was responsible for $500 million in retail and SME loans and managed the transformation of SME lending to an automated process that included implementation of credit [email protected] telephone: +1-703-747-8507

Credit Scoring

CREDIT PROCESS WORKSHOP

Credit Scoring

• Credit Scoring – Key mechanism and strategy used to evaluate SME risk. Scoring is defined as method to judge credit using a formula based on predictive data*

• Users - credit bureaus, credit providers, vendors

• Originally used - consumer/individual loans

• Now used - credit providers for non-rated corporate borrowing, leasing, other financing

* source: Credit & Management Systems, Inc


Credit Scoring

Benefits:

• Speed in the Credit Process

• Accuracy

• Quantifiable

• Fewer Bad Debts

• Favorable Regulatory Treatment


Credit Scoring

Methodology:

• SME Loan Application:

- Order credit reports and scores on owner/personal guarantors (external scoring)

- Compute a credit score on SME (internal scoring)

- Cutoff point for scores: “clear approvals” / “clear denials”

- Analysts’ valuable time focused in between the two points


Credit Scoring

Methodology (continued)

Risk/credit worthiness based on combination of:1. Traditional Scoring, 2. Credit Agency Scoring 3. Financial Statements Scoring

• Traditional (non-financial) – each factor weighted and assigned a score- Factors may include: years in operation, payment history with vendors, trade references, returned checks, litigation, judgments/tax liens, other from loan files

• Credit Agency information – each factor weighted and assigned a score- Factors may include: D&B ratings, Experian days beyond terms, etc.

• Financial Statement – various ratios are compared to sector & peer group - Liquidity, Profitability and Leverage - 3 main ones that may many sub-ratios - Sub ratios are totaled, averaged and multiplied by each weight element

CREDIT PROCESS WORKSHOPCredit Scoring

Overall Credit Score =

Traditional Score

X

Credit Agency Score

X

Financial Statement Score

X

Assigned weights


Highest Quality 1.00 to 1.83

Good Quality 1.84 to 2.66

Average Quality 2.67 to 3.50

Below Average Quality 3.51 to 4.34

Poor Risk 4.35 to 5.17

High Risk 5.18 to 6.00

CREDIT PROCESS WORKSHOPCredit Scoring - Traditional Credit / Non Financial Scoring Factors

.201.20Judgments/tax liens

Traditional Credit / Non Financial Score 2.61

.051.05Collection claims reported

.101.10Law suits

.306.05Returned checks reported

.153.05Industry credit group

.093.03Trade reference #3



.153.05Bank rating (?)

.453.15Pay history to others

.505.10Control years

.453.15Pay history to bank

ResultScore WeightFactor

CREDIT PROCESS WORKSHOPCredit Scoring - Sample Non Financial Scoring Parameters

Score Factor / Pay History to Bank

1 Pays as agreed2 Slow 1 to 15 days3 Slow 16 to 30 days4 Slow 31 to 60 days5 Slow 61 to 90 days6 Slow after 90 days

Score Factor / Control Yrs

1 Over 15 years

2 Over 10 years

3 Over 5 years

4 Less than 5 years

5 Less than 3 years

6 Less than 1 year

Scores range from 1 (highest) to 6 (lowest)

CREDIT PROCESS WORKSHOPCredit Scoring – Credit Agency Information Scoring Factors

2.50Total Credit Agency Score

.703.50.20Experian Intellscore

.6030.20Experian Days Past 16

.4020.20NACM Score 85

.6030.20D&B Paydex 75

.2010.20D&B Rating 4A2

ResultScore WeightFactor Rating

CREDIT PROCESS WORKSHOPCredit Scoring - Financial Statement Scoring Factors

2Sales / Total Assets

.937/3 = 2.33 40%Total Profitability

3Profit before Taxes / Tangible Net Worth

2Profit before Taxes / Total Assets

Profitability Ratios

.9018 / 6 = 3.00 30%Total Liquidity

2Sales / Working Capital

4Cost of Sales / Payables

3Cost of Sales / Inventory

2Sales / Receivables

4Quick Ratio

3Current Ratio

Liquidity Ratios


CREDIT PROCESS WORKSHOPCredit Scoring - Financial Statement Scoring Factors

(continued)

SUMMARY:

.60Total Leverage

2 .43Total Financial Score

.90Total Liquidity Score

.93Total Profitability

.606 / 3 = 2.0030%Total Leverage

2Total Liabilities / Tangible Net Worth

3Fixed Assets / Tangible Net Worth

1EBIT / Interest

Leverage Ratios



Example: Traditional Score = 2.61Credit Agency Score = 2.50Financial Statement Score = 2.43

1.462.430.60Financial Statement

2.49Overall

Risk Score

0.252.500.10Credit Agency

0.782.610.30Traditional

ResultScoreWeightInformation

Score Result

5.18 to 6.00High Risk

1.00 to 1.83Highest Quality

2.67 to 3.50Average

1.84 to 2.66Good

Quality

3.51 to 4.34Below Average

4.35 to 5.17Poor Risk

Sample Score Card

Loan Score Here

CREDIT PROCESS WORKSHOPExercise: Scoring SME Loan Applications

Group 1: Identify some important “Non-Financial Factors” missing from this model

Group 2: Identify some important “Financial Factors” missing from this model

Group 3: Identify & justify the top three Non-Financial & Financial Factors that are unique to each sector below. Feel free to add factors not shown in the model.

Construction contracting; Manufacturing; Service (hotel & professional services); Trading

Group 4: Propose & justify an appropriate weighting of Non-Financial and Financial Factors.

1. 40% / 60%2. 50% / 50%3. Other

Dos this answer change depending on a sector? Refer to the sectors in question #3.

CREDIT PROCESS WORKSHOPAnalytical Tools

Demonstration of Analytical Tools – An Example

Moody’s Products for Borrower Analysis

• Financial Analysis• Risk Advisor

Financial Analysis

• Steps - Input financial information • Results / Features

- Financial Reports- Ratio Analysis- Consultant Report


Demonstration of Analytical Tools (continued)

Risk Advisor

• Company Standing

• Management Quality

• Industry Risk

• Borrower Rating Summary

Integrated Risk Rating

System Design

Agenda

9:00 – 11:00

Credit Scoring

11:00 – 11:15 AM

Break

11:15 – 1:00 PM

�Integrated Rating System Design

1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM


3:00 – 3:15 PM

Break

3:15 – 4:00 PM

Recap and Q & A

9:00 – 9:30 AM


9:30 – 11:00 AM


11:00 – 11:15 AM

Break

11:15 – 1:00 PM


1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM


3:00 – 3:15 PM

Break

3:15 – 4:00 PM


Day 2Day 1

Overview

� The ratings system should differ from the risk model

� Banks must show that their risk models and rating system can be integrated so as to adequately differentiate risk

� Here we demonstrate how this integration can be performed in a systematic fashion that maximizes predictive power

� The most significant point is that ratings should begin at the individual characteristic level

�For Retail exposures this means average age, income, etc. for the pool

�For corporate and SMEs, this means balance sheet information

Basel II’s definition of an Internal Rating System

� “The term “rating system” comprises all methods, processes, controls and data collection and IT systems that support the assessment of assignment of internal ratings and the quantification of default and loss estimates.”

� Also the regulations goes on to say that banks may use multiple ratings systems and methodologies but these must documented

“Point-in-time” versus “through-the cycle ratings”

� Analysts must decide whether to rate borrowers based upon:

�Current conditions (Point in time, PIT)

�Expected credit worthiness over the life of the loan or credit cycle (Through-the-cycle, TTC)

� The decision usually depends upon the objective of the rating system (which is related to corporate priorities)

“Point-in-time” ratings

� PIT ratings are good for exposures that the bank does not intend to hold until maturity

� These ratings are appropriate if the objective is to monitor loans, establish loan reserves or allocate economic capital

�Methodology: Usually a credit horizon of one year—based upon borrower’s current and anticipated performance over horizon

� Can also be useful for derivative exposures

“Through-the cycle” ratings

� These ratings work well when the objective is to inform the (buy and hold) lending decision—particularly for first-time applicants

�Methodology: Find the worst anticipated point in the credit cycle, use stress tests to see the effects on the applicant, assign rating based upon those conditions

�This is a common rating agency methodology

� The rating is generally stable over the cycle (lends itself to infrequent assessments).

Internal ratings for Corporates, sovereigns and SMEs (and banks)

� The rating system must assign both an obligor and facility rating

�The first dimension must be a “default risk assignment”—a “score” much like a PD

� Separate exposures to obligor must be assigned to same grade regardless of transaction

�The second dimension reflects transaction-specific factors; for Advanced IRB banks, this must reflect exclusively LGD

�As we will argue, calibrating the risk model to the ratings system will achieve these objectives

Example of a risk rating system

Layout of Prototypical system

Financial Assessment

� Step 1: A financial assessment of the borrower (initial obligor rating) which sets a floor on the OR

�Must decide which entity or entities are being rated (for example, will have to take cross guarantees into account if analyzing group credit)

�A single entity with a number of facilities of different seniority will require different rating for each


�First step is akin to traditional credit analysis

�Study financial reports to determine whether earnings and cashflow sufficient to cover debt

�Want stable, positive trends

�Make sure assets of high quality and ensure obligor has substantial cash reserves (working capital)

�Debt ratios as well as access to financial markets

�Possible ability to withstand shocks and setbacks


�Regard the borrower as the Obligor UNLESS there is a guarantor — in which case, the latter may be the obligor.

�Must make sure that bank is in a superior position relative to other creditors (should be a 100% clean guarantee).

Financial Assessment Example


� Calculate a RR for each of the 4 assessment areas (earnings/cashflow, asset values/liquidity/leverage, financial size/flexibility/debt capacity) and then arrive at assessment of best overall RR

�Average should be compared to the worst rating—RR should be no better than 1 rating above worst

� RRs 2, 2, 5 have average of 3, final RR = 4

� RRs should be weighted appropriately for different industries

� Benchmark to companies in same grouping and/or industry


� Emphasize most current year’s performance with some recognition for previous years (earnings/cashflow category)

�Use EBITDA or EBIT where appropriate

� Cyclically adjust financial ratios for companies in cyclical industries (e.g., construction, real estate)

�For real estate, adjustment must be careful since asset bubbles and corrections could be prevalent

� When assessing financial size, flexibility, etc., size is very important—size of market capitalization or Market/Book (could already have a public rating)

� Use pro-forma data for private companies


� Industry Benchmarks

�Obligor should be ranked in its industry according to important and major ratios

�Rating Agencies issue guidelines for adjusting assessments according different ratios

�May want to look at historical median ratios for rated companies (shows volatility in ratio medians over time)

Step 2: Adjustment Factors for Obligor Rating

� Measure impact of qualitative factors

� Assume that this could bring about a downgrade if unacceptable

�Management decisions and changes

�Account operations, assess Management, environmental assessment, contingent liabilities.

Examining Adjustment factors

� Ask a series of structured questions

�If financial and security reporting is on a timely basis, is it in good standing?

�Does it satisfactorily explain departures from projections?

�Are credit limits and terms respected and were any requests for temporary excesses, terms etc. requested before or after the fact?

�Does the company honor obligations to creditors (are their writs, lawsuits, judgments?)

�Are management skills and scope sufficient for size of the business? (are their succession plans in place?)

Step 3A: Industry ratings summary

�Empirically, poorer performers in weak, vulnerable industries largest defaulters

�Must begin by rating each industry type on a scale of 1 – 5 (1 = minimal, 5 = high), say

�Provide industry assessment ratings scheme broken down into selective sub-industry groupings (e.g., steel products could be broken down into machinery)

�First assign a score for each of a set of criteria set by the bank (say 8)

�Sum of scores (maximum 8, minimum 40) is converted into an Industry Rating

�Group scores into 5 categories

Step 3A: Industry Assessments

�Suppose that we then have the following scale:

Step 3A: Industry assessments

�Example: 8 factors� Competitiveness: potential of industry to sell its product and

expand

� Trade environment: institutional factors that affect inter-sector trade

� Regulatory framework: legal/institutional setting (present policies and trends, industry’s ability to absorb trends)

� Restructuring: Impact of adjusting to changes in market conditions

Step 3A: Industry Adjustments (Example)

� Technological Change: industry vulnerability as a result of changing costs, changing products, range/price of competitor products

� Financial Performance: Assessment based on present level, trends, sustainability, etc.

� Long-term trends: demographics, vintage of durables and infrastructure, consumer attitudes

� Vulnerability: How sensitive industry is to macroeconomic environment (downturns, fiscal policy, exchange rates, etc.).

Step 3B: Tier Assessment

� After assigning an industry assessment we can rank the relative position of the business within its industry

�Ranked on a global basis if global industry, for example

� Tier 1 players are players that dominate the market (can respond quickly to any difficulties in Industry Assessment categories)

� Tier 2 Players are important with above-average market share

� Tier 3 are average or just below and Tier 4 are poor

Step 3C: Industry/Tier Position

�Once we have assessed the Tier, we can use a grid to tell us best possible OR

Step 4 and 5: Financial Statement Quality and Country Risk assessment

�Check that statement quality and timeliness consistent�Consider accounting firm and auditors

�Check for accounting “shenanigans”

�Assess whether there is a risk that domicile country may restrict repayment, affect terms or make environment difficult�Can develop a table to see whether this will affect OR

�Restricts “best possible” rating

Steps 6, 7 and 8: Mapping of qualitative ratings and quantitative scores

� Once we have rated the obligor in each category, we combine them and follow through a process of mapping qualitative scores to quantitative ratings

� This is conducted by using a risk model on each obligor in the portfolio

� For example, we might use a linear model like Altman to check consistency of assigning scores; this is followed by using structural model like Moody’s KMV to assess PDs and using LGD and EAD to assess exposure

� Finally, we map the rating system externally

Combining internal ratings

Qualitative Mapping of Score to Ratings

Internal risk modeling: QuantitativeScoring

Models usedon customerto obtainScore

If outside ofClass D, weanalyzefurther

Internal/External Mapping

Mapping admitscalibration ofinternal scale

Note: External scale isnot necessarily“correct”, but useful ifinternal data is lacking

External Mapping

� After testing and validation of the internal model is completed, Basel II requires that ratings be mapped to external benchmarks as an additional test

� This is the most controversial portion of Basel II (how are we to know all rating agencies are correct?)

General Methods

� If the obligor is publicly rated, the mapping process is simple: assess whether your internally assigned PD for that obligor’s category corresponds to the PD of his external rating class

� If obligor is not publicly rated, Basel Committee suggests finding proxy firms that could have similar PD

� This is likely to be inaccurate since most rated firms are very large and publicly listed, with very different access to emergency capital than smaller, non-rated firms

External Mapping Proposition

� One idea is to return to the testing/validation phase of implementation and test model on a sample of pre-existing, rated firms

� If rating assigned internally matches external ratings for a wide enough sample, the scale is sufficiently reproducing the external ratings methods

� Remaining step is to see whether assigned PD corresponds to HPD

Summary

� We have laid out a framework wherein internal risk models and internal risk rating systems can be integrated

� Primary goal of the qualitative ratings system is to introduce the “brains” to the Basel II-compliant system

� Internal risk models, even when accurate in testing, do not fully replicate the informed lending process

� Process of calibrating the ratings system with the internal risk model and these in turn, externally, is iterative

Agenda

9:00 – 11:00

Credit Scoring

11:00 – 11:15 AM

Break

11:15 – 1:00 PM


1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM

� Credit Risk Infrastructure and Risk Rating Automation

3:00 – 3:15 PM

Break

3:15 – 4:00 PM

Recap and Q & A

9:00 – 9:30 AM


9:30 – 11:00 AM


11:00 – 11:15 AM

Break

11:15 – 1:00 PM


1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM


3:00 – 3:15 PM

Break

3:15 – 4:00 PM


Day 2Day 1

Risk Rating Automation

Credit Risk Infrastructure

and

Financial Risk and Basel II Technology Components

Complexity of Data Relationships For Commercial Credits

Risk Rating Automation

– Key Benefits:

– Controlled execution of rating methodology

– Consistent capture of data

– Timely / single point of access to disparate data sources

– Execution of complex / repetitive calculations

Sample Group of Solution Vendors

Prim

ary V

en

do

r

√Cognos

√√

Experian

√√

Oracle/ PeopleSoft

Da

ta M

gt &

Re

po

rting

√√

D&B

Exte

rna

l Da

ta &

Cre

dit

Mo

de

ls

√

√

√

Reporting

√

√

√

Capital

Calculation

√

Terradata

√√√Moody’s/K

MV

√√SAS

√√√√√

Algorithmics

√√√√

Reveleus*

Other

Portfolio Opti,RAROC,EVA Loan

Pricing

Automation

&

Workflow

Credit

Risk Models

Engine

Enterprise Architecture,

DW&

Data Model

External

Historical Loss Data &

Benchmarking

Solution

Vendors

Key issues include:• One or many systems • Cost

• Implementation timeline• Internal support/resources

*Reveleus is a subsidiary of Oracle and thus relies on their EDW capabilities

Gartner Solution Magic Quadrant

Customer Segments and Vendor Positioning

Source: Celent Analysis

Vendors in Top 10 Banks

Linked to PowerPlay, MicroStrategy, and Brio. Also linked to SAS and COGNOS

eMFAKeybank (Cleveland, Ohio)

10

SASHSBC North America Inc. (Buffalo, N.Y.)

9

Moody's KMVSASPeopleSoft EPMPrism (In house system)

Suntrust Banks, Inc. (Atlanta, Ga.)

8

AFS (Benchmarking)U.S. BC (Cincinnati, Ohio)

7

Zoot (mortgage decisioning)

Washington Mutual6

ReveleusCognizant? Reveleus (Capital calculation)

ReveleusWells Fargo & Company (San Francisco, Calif.)

5

AFS (Benchmarking)Reveleus / Microstrategy, SAS (customer analysis)

ReveleusSunGard’s AdaptivWachovia Corp. (Charlotte, N.C.)

4

ReveleusReveleus / Cognizant

Citigroup (New York, N.Y.)

3

Microstrategy, Actuate (client-side reporting at JP Morgan Fleming)

spending over $100MM to develop in house credit risk management system

J. P. Morgan Chase & Company (New York, N.Y.)

2

AFS (Benchmarking)Sungard / Actuate (card management and reporting)

Bancware Capital Manager (SunGuard)

SungardBank of America Corp. (Charlotte, N.C.)

1

BenchmarkingReportingCapital SolutionCredit data warehouse

Credit Risk Rating System

Name (city, State)Rank

Agenda

9:00 – 11:00

Credit Scoring

11:00 – 11:15 AM

Break

11:15 – 1:00 PM


1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM


3:00 – 3:15 PM

Break

3:15 – 4:00 PM

� Recap and Q & A

9:00 – 9:30 AM


9:30 – 11:00 AM


11:00 – 11:15 AM

Break

11:15 – 1:00 PM


1:00 – 2:00 PM

Lunch

2:00 – 3:00 PM


3:00 – 3:15 PM

Break

3:15 – 4:00 PM


Day 2Day 1

Day 2 Recap and

Q & A

Credit Process WorkshopNotes from break-out sessions

with bankers

• Banker Group 1: Identify some important “Non-Financial Factors” missing from this model

1- Legal Form - sole proprietorship tends to be more risky than partnership

2- Concentration on one supplier

3- Customer Base – same concentration risk

4- Management Ability

5- Reputation

6- Age of Business – older the better

7- Market and Completion


with bankers

• Banker Group 2: Identify some important “Financial Factors” missing from this model

• SME / Credit

• GAPS

• Credit History

•* Profitability ratio

• Profit margin = sales/cost of Good Sold

• ROA = return on assets

• RoE = return on equity


with bankers

* Leverage rations________________Debt/EquityDebt/ Total assets

* Growth Ratios ________________Growth of sales Growth of ExpensesProfitability of default __________________* Z score * Cost flow – Historical

_ ProjectionsZ Score


with bankers

• Banker Group 3: Identify & justify the top three Non-Financial & Financial Factors that are unique to each sector below. Feel free to add factors not shown in the model.

• Construction contracting; Manufacturing; Service (hotel & professional services); Trading


with bankersSector Non Financials Financials

Construction Control yearsPay history to Bank Pay History to others- Reputation

Leverage RationLiquidityF-Assets- Capacity- Inventory

Manufacturing Know-howCollectionProduct Quality

Leverage RatioProfitabilityLiquidityInv .turnover

Service Pay history Control yearsLaw Suits Judgments Reputation

Cross Margin Liquidity Owners

Ret worthReceivables

Trading Pay History Collection Trade referenceReputation

Liquidity ProfitabilityOwners

Net worth


with bankers

• Banker Group 4: Propose & justify an appropriate weighting of Non-Financial and Financial Factors.

1. 40% / 60%

• 2. 50% / 50%

• 3. Other

• Dos this answer change depending on the sector? Refer to the sectors in question #3.

• Comparative Analysis Data

• 1- Industry 2- Peer Group


with bankers

JOD

0 – 50 K

51-100 K

101-250 K

N.F Fin.

8

0 : 20

N.F Fin.

70 : 30 N.F Fin.

60 : 40

N.F Fin.

70 : 30

N.F Fin.

60 : 40

N.F Fin.

50 : 50

• Any loan exceeding 100 k must produce audited financial statement

irrespective of the no

• . of years in business

• In reference to the question, the loan policy should address specific sectors.

Loan Amount


with bankers

Page No. 6

Page no. 7. Aggregating internal and external loan exposure

Dominick

Antonelli

Bank Parking Comm

Garage Real Estate

Residential

Office shop center

Multi - Family

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