Title Here in Title Case and up to Three Lines 32pt.

Title Here in Title Case and up to Three Lines 32pt.

Small Business Credit Scoring An Empirical Analysis of the Viability of Pooled Data SME Scoring Models in Latin America Presented at the Conference on Small and Medium Enterprises, Washington, D.C., Oct. 15, 2004 Margaret Miller 1 Project Objective To determine if pooled data SME credit scoring tools, which have proved very successful in the U.S. and in a few other select markets, could be developed for large emerging markets in Latin America 2 Relevant Literature on Credit Reporting

Credit reporting can facilitate access to credit Positive relationship between private credit / GDP and credit reporting (Doing Business) Credit reporting reduces credit constraints on firms (Galindo & Miller 2001, Love & Mylenko 2003) Credit reporting reduces the impact of bank concentration on access to finance (Beck, Demirguc-Kunt & Maksimovic 2004) 3 Relationship Lending in the Small Business Credit Market Old paradigm SME loan market focuses on

relationship lending (Petersen & Rajan 1994, Berger & Udell 1995, Miller 1995) New paradigm SME loan market segmented with local lenders employing relationship lending technologies and national lenders using automated scoring (Petersen & Rajan 2002, DellAriccia & Marquez 2003, Hauswald & Marquez 2002, Brevoort & Hannan 2004) Newest paradigm? Many lenders using both technologies? 4 Literature on Small Business Credit Scoring (SBCS) Large banks in the U.S. were more likely to adopt SBCS first (Akhavein, Frame & White 2001) U.S. banks that adopted SBCS increased their SME lending by 8.4% on average about $4 billion in increased lending per institution (Frame, Srinivasan & Woosley 2001)

Increased lending volumes from SBCS served to increase access to marginal or riskier borrowers (Berger, Frame & Miller 2002) 5 Significant Increase in Number of SME Loans Extended in U.S. Since Introduction of SBCS U.S. Commercial Lending, Dollars in billions, numbers in millions Value of Loans < 100k Number of Loans 2003 125.7 14.1 2002 128.9 15.7

2001 126.8 10.8 1999 113.9 7.7 1997 108.2 6.7 1995 100.4 4.9 Value of Loans < 250k Number of Loans

224 14.9 225 16.5 218.4 11.6 195 8.4 178.8 7.4 163.9 5.4 6 Small Business Scoring Still

Limited in Developing Countries Only largest financial institutions have adopted SBCS Have funds to invest in expert or custom models View SBCS and their SME portfolio data as key elements of their competitive edge Lenders are reluctant to share data, especially on the SME market segment; not used to working in common for a pooled model Difficult for external technology providers to create consortiums 7 Deficiencies in the small business lending Identify improvements in the banking and lending

industry to allow small businesses growth and development Manage overall portfolio risk Streamline operations for increased cost efficiencies Increase number of profitable relationships Identify predictive data elements to analyze the credit risk 8 How scoring technology can help the lenders? Reduces cost by increasing efficiency and speed Make consistent ranking of risk and objective decisions Accurate risk prediction

Majority of risk identified at origination! Competitive edge Faster response times Better risk assessment 9 Small business definitionUnited States Annual Sales of up to $5 million Credit of up to $250,000 Types of Small Businesses:

Sole Proprietors Partnerships Corporations 10 Small Business Scoring Service (SBSS) in the United States Fair Isaac partners with Robert Morris Associates (RMA) 17 banks each contribute 100 goods, 100 bads, 100 declines Precoding sheets filled out by hand Paper credit bureau reports Fair Isaac data entry staff creates electronic database

1995 - Fair Isaac SBSS releases the first empirically derived commercial scorecards 11 Small Business Pooled Models Improvements Over 250,000 small businesses contributed by 25 banks Data extracted electronically from application processing and master billing file systems 100% availability of consumer bureau information Business data provides increase in predictive power Application, Business reports, Financial statements 2001 - Fair Isaac releases second generation of commercial scorecards Currently building the New Small Business Pooled Models

12 Small business scoring pooled models in Asia Pooled Models in Japan Over 3,500 small businesses contributed by 13 banks Data transferred from application processing and master billing file systems and availability of consumer bureau information Business data provides increase in predictive power Application Financial statements Demographic information

Currently building pooled models in Hong Kong 13 Definition of Small Business in Latin America There is no consistent definition between lenders in Latin America. COLOMBIA Number of Employees up to 200 Annual Sales of up to $1 million Credit of up to $200,000 Types of Small Businesses:

Sole Proprietors Partnerships Corporations MEXICO Number of Employees up to 100 Annual Sales of up to $500,000 Credit of up to $200,000 Types of Small Businesses:

Sole Proprietors Partnerships Corporations 14 Distribution by business activity COLOMBIA MEXICO 7% 11% 9% 12%

3% 8% 8% 18% 30% 48% 15% 2% 4% 16% 8%

1% 15 Acceptance and booked rates 90% 80% 70% 60% 50% Acceptance Rate Booked Rate 40% 30% 20% 10% 0% Colombia

Mexico 16 Distribution of delinquencies 3.0% 2.5% 2.0% One Cycle Two Cycles Written Off 1.5% 1.0% 0.5% 0.0% Colombia Mexico 17

Application processing time 12 10 D A Y S 8 6 4 2 0 Colombia Mexico 18

Pooled data development sampling A random representative portion of accounts with known payment behavior plus declined accounts Data provided by all institutions participating in the pool Predictive information and performance information 19 Data sources - Personal information about principals Application Financial information Consumer credit reports 20 Value of data

High Business Value Personal Low Small Size of Company Large 21 Report for participants Lending practices

List of valuable variable that could be use for future model development or strategies Summary of individual portfolio performance Validation of questionnaire responses 22

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