Microfinance Bureaus : Balancing Vision and Pragmatic Solutions

Microfinance Bureaus : Balancing Vision and Pragmatic Solutions Regional Conference on Credit Reporting in Africa Organized by the World Bank and the IFC Break-out Session on Microfinance Bureaus Cape Town, South Africa October 6, 2006 Mehdi Dutheil, Regional Director

AGENDA THE CASE FOR CREDIT REPORTING IN THE MICROFINANCE SECTOR INTEGRATED CREDIT BUREAUS: LONG TERM VISION AND PRESENT DAY REALITIES CASE STUDIES: INDUSTRY-LED VS. GOVERNMENT-LED MICROCREDIT BUREAUS PERSPECTIVES

ARE CREDIT BUREAUS REALLY USEFUL IN MICROFINANCE ? • Banks make consumer loans using credit-bureau data for salaried borrowers with an automated, “high-tech” credit scoring approach  Quantitative data are essential, hence credit bureaus are a priority • On the contrary, microfinance enterprise loans are based on an individualized, labor-intensive “high-touch” approach to get data directly from the applicant and analyze the cash flows and personal character of the microentrepreneur * • self-employed poor cannot document income and credit history • to compensate, MFIs send out credit officers to applicants’ homes  Consequently, credit reporting and credit bureaus used to be deemed secondary in the microfinance sector (*) Hans Dellien, WWB, and Mark Schreiner, MRM, December 2005

BEFORE CREDIT BUREAUS: THE BOLIVIAN CRISIS IMPACT OF NOT HAVING CREDIT REPORTING: THE EXAMPLE OF BOLIVIA Bad Debt Rate - Bolivia In the late 1990s there was a crisis in the Bolivian microfinance sector due to over indebtedness of the clients The main cause for the crisis was the lack of information sharing tools. COOPERATIVES

HOW IS CREDIT INFORMATION USED? In credit underwriting In pre-selection In portfolio management • To sort out bad borrowers up-front • To offer better conditions to good borrowers • To reduce the cost of credit • To identify bad borrowers • To price risk accordingly • To use automated / semi-automated underwriting tools like credit scoring • To identify deterioration of existing borrowers • To avoid aggregation of bad debt among a number of financial institutions • To collect the most risky debt first

BENEFITS OF CREDIT BUREAUS IN THE MICROFINANCE SECTOR AT THE CLIENT’S LEVEL • Increased efficiency in the evaluation of a loan can result in faster loan processing • Clients with a good record can get preferential services and lower prices • Clients are empowered to apply for credit in another location • Default prone clients have the desire to obtain a good report and will hence be encouraged to pay their bad debts • Lower risk of over-indebtedness by clients

BENEFITS OF CREDIT BUREAUS IN THE MICROFINANCE SECTOR AT THE INSTITUTIONAL LEVEL: BETTER INFORMATION SHARING AND DECISION MAKING • More reliable decision making • Minimizing risk because of a better visibility on borrowers’ past and ongoing default history and on their current outstanding balance of payments in different institutions • Reducing transaction costs as it facilitates the analysis and quantification of credit risk • Avoiding the aggregation of bad debt by borrowers among a number of financial institutions • Increasing the number of loans granted as potential borrowers who were before excluded from the system because of the lack of information on their concern become beneficiaries

BENEFITS OF CREDIT BUREAUS IN THE MICROFINANCE SECTOR AT THE SECTOR LEVEL: BETTER REGULATION AND INCREASED COMPETITION • Facilitates financial sector’s supervision (Public Credit Registries in particular) • Provides data for economic research and microfinance regulation improvement • Facilitates the entry of new players in the market, such as banks willing to downscale into microfinance

BENEFITS OF SHARING NEGATIVE AND POSITIVE INFORMATION REDUCTION OF DEFAULT RISK AT THE INSTITUTIONAL LEVEL INCREASED ACCESS TO CREDIT AT THE CLIENT’S LEVEL Percent decrease in default rate Percent of applicants who obtain a loan 12% decrease in default rate 90% increase in access Negative information only Negative & positive information Negative information only Negative & positive information Simulated credit defaults assuming an acceptance rate of 60% Simulated credit availability assuming a target default rate of 3% Source: Barron and Staten (2000)

BENEFITS OF CREDIT BUREAUS IN THE MICROFINANCE SECTOR CREDIT BUREAUS AND SUSTAINABLEPOVERTY ALLEVIATION IMPROVEMENT OF MFIs FINANCIAL VIABILITY SETTING UP A CREDIT BUREAU INITIAL FUNDING MFIs’ SUBSCRIPTION TO CB CB SELF- FINANCING REDUCED POVERTY REPAYMENT SUSTAINABILITY OF THE CREDIT BUREAU INCREASE IN THE TOTAL NUMBER OF MICROLENDING BENEFICIARIES INCREASE IN THE PROPORTION OF BENEFICIARIES WITH REPAYMENT CAPACITY Source: Développement de la première Centrale des Risques sur Internet pour les Institutions de MF au Bénin, PlaNet Finance

THE VISION OF AN INTEGRATED CREDIT BUREAU • Full information sharing between financial (banks, consumer credit institutions, MFIs) and non financial institutions (retailers, telecom operators, utilities, etc.) • prevents clients over-indebtedness • fosters profitability at the financial system level • In the long run, global and specialized private operators should be better positioned to ensure maintenance and evolution of the credit reporting system and bring technological and marketing innovations: real time updates, mobile access, applicant scoring, payment default alerts, etc. • Depending on countries, the supervision of the credit bureau can be taken care of either by the industry itself or by a public entity (Central Bank, Supervision Commission, etc.)

THE CASE FOR INTEGRATED CREDIT BUREAUS THE IMPORTANCE OF SHARING INFORMATION ACROSS SECTORS “Positive& Negative” Types of Information “Negative Only” Sources ofInformation Highpredictiveness (e.g. US, UK, Italy, South Africa) “Full” (information shared by banks, retailers, NBFIs, mobile operators) Lower predictiveness (e.g. Australia, Brazil) “Fragmented” (e.g. information shared among banks only or retail only) Lower predictiveness (e.g. Poland, Czech Republic) Lowest predictiveness (e.g. Morocco, South Korea) Source: Microfinance and Credit Bureaus, Peer Stein (IFC)

PRESENT DAY REALITIES OFTEN HAMPER INTEGRATED CREDIT BUREAUS IMPLEMENTATION • Many MFIs have very basic information systems (some are simply not computerized), which cannot compare with those of banks • Microcredit bureaus business models are usually based on a big number of inquiries for small loans. Therefore, the amount charged /inquiry cannot be the same as the one charged for banks • Because of short term loan cycles, MFIs need more frequent data updates and payment default after 30 days, rather than 6 months • A large part of MFIs’ staff being poorly educated, the ease of use of the Credit Bureau’s application is more important than the number of functionalities • The key for inquiries is different between MFIs (informal businesses identified by name and ID number) and banks (mostly formal businesses identified by corporate number) • In a multi-sector credit bureau initiative, achieving a wide-ranging buy-in by all the players in a country is possible only if credit reporting has already reached sufficient maturity

INDUSTRY-LED VS. GOVERNMENT-LED MICROCREDIT BUREAUS The role of the National Regulator differs widely according to countries: • In many countries, Microcredit Bureaus initiatives stem from the industry and do not require investments in IT in the short run : • In Mali’s « Fleuve Niger » region, MFI executives hold an informal meeting and exchange their lists of delinquent clients. No software was developed • In Haïti, MFIs have developed an Microcredit Bureau based on an Access database restricted to negative information • In Mozambique, there is both: • a Credit Bureau based on SAP and supervised by the Central Bank, to which leading MFIs contribute monthly as well as banks, and • an informal exchange of delinquent clients lists (Excel) between MFIs’ directors (more-up to-date) • In Jordan, Tunisia and Egypt, legal difficulties impede the set up of banking / microfinance credit bureaus

Source: World Bank 2002

CASE STUDY: BENIN MICROCREDIT BUREAU IMPLEMENTATION CONTEXT OF MICROFINANCE IN BENIN • 400,000 microfinance beneficiaries out of a total potential number of 4,000,000 beneficiaries • High level of competition with around 400 MFIs competing on the same segments of the market  risks: over-indebtedness of clients and increased default on payments

A PIONEERING INITIATIVE INTRODUCTION TO THE CREDIT BUREAU CREATION PROJECT • The idea of a credit bureau was first launched by 5 local MFIs including PADME, FINADEV and Vital Finance which realized in 2001 that their portfolio was deteriorating • The objective was to consolidate portfolio quality by sharing information on payments overdue for more than 30 days via an internet system

MAIN AREAS OF ACTION IN THE PROJECT PROJECT ROADMAP • Office set-up and equipment • Design of the data base • Establishment of procedures • Training of credit bureau’s administrator • Creation of the website • Training of MFI personnel • Choice of legal statute and registration of the statute • Maintenance of the website • Awareness campaigns to convince other MFIs on the advantages of becoming a member of the credit bureau MAIN CHALLENGES ENCOUNTERED • Technology challenge: not all MFIs in Benin are equipped with the adequate technology (internet…)  necessity to provide relevant technology and diversify the information channels • Data collection challenge: it took time to make sure that the MFIs had a common vision on the information they need and the way to collect it

HOW THE BENIN CREDIT BUREAU WORKS MFIs MFIs 3 tools to access information • Internet • CD-ROM • PDA (Personal Digital Assistant) • Monthly filling and actualization of INFORMATION GRIDS listing the number of overdue payments of more than 30 days. Files are sent to the CB Transmission of the information required CREDIT BUREAU Confidential information gathered on each borrower • Personal information on each borrower • Occupation • Number of credits obtained • Nature of outstanding credit • Centralization of the information • Consistency check of the information collected • Information processing • Information storage in the CB database

EARLY TANGIBLE RESULTS LOAN OFFICERS • Better knowledge of the applicants enabling a better decision making An average of 150 inquiries per loan officer each month MFIs • Better quality of lending portfolio • The number of applications rejected has significantly decreased • Participating MFIs have reported better discipline amongst the clients, as they became aware that a bad credit history will deny them future access to credit

DECREASE IN REJECTED APPLICATIONS AFTER THE IMPLEMENTATION OF THE CREDIT BUREAU

CONSEQUENCES OF THE SUCCESS OF THE PROJECT • The World Bank has granted the budget required to extend the project to 17 MFIs in 2002 • Following the success of this experiment, it was decided to further develop the credit bureau in a 3-year program, with the objective of bringing it to financial viability and increasing the number of members to 40 • Today, the ownership and responsibility of the project has been transferred to Consortium Alafia, the Benin Microfinance Association • The Credit Bureau is now operating in 6 provinces, through local agencies • In July 2006, there were 20,000 clients in the database • Discussions have been held with the BCEAO in order to transfer the Credit Bureau in the context of a regional Credit Bureau project

KEY LEARNINGS • Microfinance credit bureaus are effective tools to prevent delinquency, even when the budget allows onlyfor the sharingof negative information • Very basic technologies can be sufficient in the short-to-mid-term • Progressive buy-in of MFIs can be ensured by • offering a highly professional service • using technologies adapted to MFIs capacity • proposing an adequate fee structure • In case of management of the credit bureau by the professional association and moderate maintenance costs, the fee can be included into the membership fee to the association • Ownership and leadership issues must be tackled at the start of the project

CASE STUDY: THE MOROCCAN CREDIT BUREAU IMPLEMENTATION CONTEXT OF MICROFINANCE IN MOROCCO • 12 MFIs in Morocco, with a microfinance market characterized by a high rate of repayment: 99% average • This rate is deteriorating due to increased competition between MFIs covering the same areas and an increase in the number of cross-debts

INTRODUCTION TO THE CREDIT BUREAU CREATION PROJECT • The Moroccan Credit Bureau, which began its operations in 2005, is mostly aimed at preventing crossed loans to clients whose loans are not delinquent yet. Hence the need for • negative and positive information • enabling access to the database for all the Moroccan MFIs (from the largest to the smallest) • The project was supervised by a work group comprising the MFIs, their federation (FNAM) and PlaNet Finance Maroc. The Grameen Foundation USA and USAID also took part to the project design • An estimated 1,000,000 yearly inquiries are needed to make the project viable

CREDIT BUREAU DEVELOPMENT: INITIAL STEPS Development phase • Analysis of each of Morocco’s MFIs capacity to provide the Credit Bureau with the required data, and identification of the actions needed to develop this capacity (beg. 2004) • Identification of information that can be exchanged • Establishment of the conditions of contract • Evaluation of the financial viability of the CB / business plan • Call for tender for the choice of an information system provider of services • Choice of the IS service provider in cooperation with the MFIs • Parameter settings (beg. 2005)

CRITERIA USED IN THE CHOICE OF AN INFORMATION SYSTEM SERVICE PROVIDER • Choice of a provider with existing experience in the management of data • Choice of a provider not using sub-contractors, which guarantees the continuity of the assistance • Choice of a partner proposing an IS capable of evolution,in order to process one million loans in the near future • Choice of simple tools that can be used by all MFIs even with basic IT equipment

HOW THE MOROCCAN CREDIT BUREAU WORKS: ARCHITECTURE Clients Database Credit Bureau Server Software: - Application server TOMCAT 4.1 - Application CB-CLIENT - FTP SERVER Software: - Application server TOMCAT 4.1 - Application CB-ADMIN - FTP SERVER MySQL 4.1

HOW THE MOROCCAN CREDIT BUREAU WORKS: UPDATES Initially: up-loading of all relevant information by all MFIs participating in the project Regularly: • Entry of all new borrowers and loans • Changes in current borrowers and loans details • Loan cancellation How : • From the MFI Head Office or authorized branch locations • Interactive : direct uploading of information from MFIs’ databases by the Credit Bureau • Batch : Preparation and sending of data by the MFIs for treatment by the Credit Bureau • Follow-up of operations by delivery of notification with identification number

HOW THE MOROCCAN CREDIT BUREAU WORKS: INQUIRIES The credit Bureau can be searched at all times from the Head Office or authorized MFIs branches • The National Identification Number is the default search key • Inquiries can be carried out: • On the web • By batch : after information is sent to the Credit Bureau by the MFIs, detailed reports are sent back • By SMS • Contents of Results Page : • Identification of the borrower’s information • Identification of loan information • Various tools for visualization of results

HOW THE MOROCCAN CREDIT BUREAU WORKS: ADMINISTRATION • Security • Login and encrypted password • Verification of contents • Encrypting of exchanged information • Server protected from external intrusion • Level of Interaction: • The role of each user is clearly specified: manager, administrator, updater, enquirer • Archives of exchanged information • Reporting on Credit Bureau usage frequency

Operational phase Once the project is fully operational, PF Morocco will help institutionalize the Credit Bureau and will share the code with the selected CB manager Central Bank Options of management for the CB Consortium of member MFIs (“Economic Interest Group”) National Federation of Microcredit Associations Specialized private entity or third party (Experian, etc.)

KEY LEARNINGS • The institutional framework must be set up precisely even before setting up the technical framework • The technical side of it is quite simple • The buy-in from MFIs top management is essential • The ease of use of the Credit Bureau’s application is important, as a large part of the MFIs’ staff is not highly educated

CREDIT SCORING, A POTENTIAL FOR MICROFINANCE DEFINITION A quantitative method used to predict repayment risk based on the performance of past loans with characteristics similar to current loans. By use of a scorecard, points are assigned to the attributes of an applicant, and the sum of the points is the “score”, with more points meaning more risk. OBJECTIVES Evaluate the risk from all potential customers when applying for credit, through the forecast of delinquent accounts or default of payment

BENEFITS OF CREDIT SCORING (1/2) AT THE CLIENT’S LEVEL: A FAIR EVALUATION SYSTEM • Clients are evaluated on non-subjective data through a well defined methodology • Better pricing of loans • Increased efficiency in evaluating loans can result in faster loan processing • Default prone clients who wish to obtain a good report will have an incentive to pay their bad debts • Lower risk of over-indebtedness by beneficiaries

BENEFITS OF CREDIT SCORING (2/2) AT THE INSTITUTIONAL LEVEL • More reliable decision making through better knowledge of the clients’ past behavior • Better pricing of loans and provision against loan losses through the analysis of individual client risks • Clear segmentation of population by score and delinquencies that helps design better strategies for delinquency prevention and for marketing • Increase in the transferability of borrowers from one institution to another

CASE STUDY OF CREDIT SCORING: MEXICO THE CONTEXT • Mexican MFI with more than 100,000 clients. • 40 branches • Assets over 100 millions USD PRECONDITIONS FOR THE SUCCESS OF THE PROJECT • Consolidated MIS • Commitment of Top Management

CASE STUDY OF CREDIT SCORING: MEXICO SITUATION BEFORE SCORING • A fragmented credit process • Lack of standardization in decision making • Authorization delays (up to 10 days) • Impossible to measure ex - ante risk

Medium Risk High Risk Low Risk CASE STUDY OF CREDIT SCORING: MEXICO The scorecard can identify ex-ante risk from groups where the ratio of good to bad clients is almost 35/1 to those high risk groups where the ratio is 2/1

CASE STUDY OF CREDIT SCORING: MEXICO • A scorecard was implemented in the MIS of the MFI • The MFI also have an Excel tool for testing the model

CASE STUDY OF CREDIT SCORING: MEXICO RESULTS OF THE CREDIT SCORING PROJECT • Credit in 24 hours • 80% of the applications with immediate results • Reduction of 35% of credit cost • Reduction of bad debt rate as analysts only focus on relevant applications (medium or high risk, leaving the rest to the score) • Standardization of risk

CONCLUSION: KEY SUCCESS FACTORS KEY SUCCESS FACTORS FOR MICRO CREDIT BUREAUS • Ensure that MFIs are ready for a credit bureau based on their IT systems and credit underwriting processes • Work with experienced credit bureau operators and consultants • Ensure that MFIs are given sufficient support and training to include credit reports and value-added services into their credit underwriting processes • Collect both positive and negative information about borrowers in order to reduce information asymmetry • Adjust credit bureau inquiry prices to the MFIs financial capacities

Microfinance Bureaus : Balancing Vision and Pragmatic Solutions