MICROFINANCE INSTITUTIONS/RURAL CREDIT REPORTING. Colin Raymond / Mauricio Zambrana Kuala Lumpur November, Session 9

Transcription

1 MICROFINANCE INSTITUTIONS/RURAL CREDIT REPORTING Colin Raymond / Mauricio Zambrana Kuala Lumpur November, Session 9

2 Presentation contents Background to Microfinance Case Study (MicroMicro) Present their findings/recommendations. Indian Microfinance Credit Reporting Case from the MENA region Global perspective Case study review (MicroMicro) Q & A 2

3 Poverty is unnecessary - Mohammed Yunus 3

4 Why Microfinance? Profit Loss Loan/Deposit Amount There is a break-even point in providing loans or deposits below which banks lose money on each transaction they make. Poor people usually fall below that break-even point. A similar equation resists efforts to deliver other financial services to poor people. 4

5 Small and micro enterprises have limited access to formal financial services. Under certain circumstances, an improvement on the delivery of financial services to these enterprises could accelerate their growth, and help this population segment to get out of poverty. There are many difficulties to provide financial services efficiently. The main problem originates in information deficiencies. Information asymmetry Moral hazard Absence of appropriate legal framework to execute the contracts Lack of financial infrastructure 5

6 Microenterprise activity differs from formal production by the spatial dispersion of the units, the heterogeneity of the enterprises themselves, their resources and their production methods, and the variability of its activity over time (seasonality). The micro entrepreneur is going to credit those sources that impose lower transaction costs, and would rather pay a higher interest rate, provided that transaction costs are competitively low. The magnitude of transaction costs depends on the distance between the creditor and the debtor, not only geographical distance, but also cultural. Credit technology is a set of actions and procedures that a micro-lender adopts to solve these problems 6

7 Credit risk Management Short term loans Credits granted gradually Group-lending Credit risk widely distributed among thousands of customers with small amounts Cash flow analysis based on loan officer s assessment Operational management customers per loan officer Loan officers retribution based on productivity Loan portfolio managed conservatively (no refinancing, bad debt provisions over 200%, 30 days past due loans provisioned by 100%). Loan officers with bank experience not hired 7

8 Group Loans Village Banking Individual Loans Payment behavior affected by group pressure Payment history not always recorded at individual level Banco Compartamos (México) Interest Rate Distribution 8

9 Microfinance Lifecycle EARLY STAGE INTERMEDIATE STAGE MATURE MARKET LENDING TECHNOLOGY Village Banking Group-Lending Village Banking Group-Lending Individual Loans Individual Loans mostly LOAN AMOUNT $US $US 150-1,000 $US ,000 CREDITORS PER LOCATION CREDIT DESTINATION Mostly only one, or none Business Some locations with two or more creditors Business and consumption Most locations with two or more micro lenders Business, consumption, housing FUNDING Grants Grants, Loans Saving accounts, Loans CREDIT RISK ASSESSMENT Customer s neighbors, colleagues, and providers Internal credit scoring, black lists Credit bureau services 9

10 Banana Skins 2012 Survey Top 3 Risks Globally Over-Indebtedness, Corporate Governance, Management Quality Report raises question Are credit bureaux the answer? Pros most respondents blamed absence of centralized CIBs as CIBs help identify potential risks and help client build credit history Cons - Effectiveness of CIB depend on MFI willingness to use them Bureau data not complete MFIs not following rigorous practices to avoid over indebting clients Microfinance Banana Skins 2012 The CSFI survey of Microfinance Risk 10

11 MicroMicro 11

12 Solution to Question 1 Income Statement (Current) Income Statement (Using CB Services) Financial income 1,759,421 Financial income 1,759,421 - Financial expenses (funding) 755,307 - Financial expenses (funding) 755,307 Gross income 1,004,114 Gross income 1,004,114 - Operational cost 392,484 - Operational cost 427,484 - Bad debt provisions 576,886 - Bad debt provisions 443,596 Net profit /loss 34,744 Net profit /loss 133,034 12

13 Technology needed for MFIs: Basic accounting Data transmission Most MFIs prefer having a tool that can handle the extraction and transformation activity Quality and adequacy of data was an issue especially in identification data such as ID data, complete address, etc. Identification and de-duping of borrowers Economical costing of Credit Information Report Incorporating the group concept in credit information sharing 13

14 CHALLENGES CURRENT GAPS WHAT NEEDS TO BE DONE Use of credit bureaus Early in the lifecycle on effective use of credit bureaus in decisioning more information vs. accurate information Use of data to make differential decisions rather than classification into black and white Technology Internet access in remote branches Limited number institution using loan origination systems and automated decisioning systems Data Training and awareness Data Capture Low understanding of the importance of data quality and accurate data capture Data Submission Regular & timely submission of data Ensuring complete submission of data Accurate reporting of changes in the data Continuous changes in branches and account nos. SHG data not available in the data submission Awareness of Information provided by Credit Bureaus and its importance in credit decisions for MFIs for risk management & regulatory compliance Score/Risk based pricing Best practice transfer from banking Risk ranking of bureau scores Mobile Reports Work with bureaus and software providers to create low cost solutions for interfacing and end to end decisioning systems Investment in technology to ensure the branches are connected and there are basic checks in place on data capture MFIs to continuously work for improved data collection Sharing of SHG data by the banks and state governments (SHG/MFI overlap 80%) Awareness of data quality issues and sensitization of the teams to the importance of accuracy of reporting. Partnership with Bureau, MFI associations and institutions like IFC for creating awareness on credit bureau importance & need for financial inclusion Source: Equifax India

15 Complete data submission DOB ID Phone Address Name Zip Name Age Address Zip ID Phone Ensure all credit institutions participate in the bureaus Ensure that all institution submit complete data Data Quality Address Address Format is not standardized Regional Language References Name Vary from region to region Name DOB Phone Address ID Phone Name DOB ID Address Influenced by religion and caste Many instance of names with just Initials ID Population Not every one has to have one Socio-Economic Condition Joint Family Highly populated Source: Equifax India 15

16 Three women approached an MFI seeking a new loan and as part of their credit policy, the MFI obtained a credit report. They found delinquencies in loans from another MFI. Upon being presented with this discovery, the applicants first went back to the other MFI, corrected the default, and returned with updated statements. Value: MFI Bureau check improves borrower behavior, and reduced delinquency for the entire community Source: High Mark Credit Information Services

17 Based on credit report, this MFI noted the overwhelming majority of their borrowers provided false declarations about not having borrowed from other MFIs. This MFI started to inform borrowers that they knew which other MFI they had borrowed from. In just a few months, false declarations came down from 92% to about 7% Value: MFI Bureau check keeps the borrowers more honest Source: High Mark Credit Information Services

18 Bolivia: Portfolio at Risk (PAR) by type of MFI: % 10% The credit bureau started operations on August, Regulated MFIs were already sharing credit information through a public registry. 8% 6% 4% Regulated MFIs Non-Regulated MFIs Loan Portfolio: Regulated MFIs : $US 3,015 Millions Non-Regulated MFIs: $US 326 Millions 2% 0%

19 Contacted 120 MFIs across 13 states Varying size portfolios from < than 1,000 to > than 50,000 members 34 respondents portfolio mix SHGs, JLGs and individual loans Most are computerized and have data available for bureau submission Key concerns Lack of awareness of statutory requirement Lack of awareness about the actual process involved in terms of how data will be submitted and how data can be accessed. Belief that benefits of CB are for larger MFI not smaller ones Cost of membership and integration is uneconomical given the thinning spreads, the capped margins and escalating operations cost Changes in internal credit evaluation processes as well as capability of the ground staff to handle these changes 20

20 What if I do not have all the data fields that you are asking for? Who will have access to my data? Can I decide on what data to submit, when to submit, whom to submit?

21 What if I am unable to submit data for a particular period? Can I access data from the non-mfi bureau database? How do I know about simultaneous loan applications by a borrower? Is my loan applicant shopping for loans from MFIs?

22 MFIs are non regulated; don t take deposits from the public, and for them it s not mandatory to report/consult to the credit bureau. Access to the only credit bureau is not very easy: Subscription fee, annual fees; cost of inquiries is perceived as very expensive by MFIs Inquiries made trough leased lines only (no inquiries trough the Internet) To report data MFIs have to buy an expensive software license (validation tool) and use the leased line to submit the data, as well. Minimum batch queries accepted is 1,000. Standard credit reports of 9-12 pages For most MFIs, to get involved in the credit reporting system is not a priority yet, since they are not aware of the benefits, and the PAR in most cases is under control. Some MFIs are sharing credit information (partially) through the Microfinance network, and cross-lending is virtually nill. Just a few MFIs report (partially) to the credit bureau and none of them inquires extensively 23

23 MFI LOANS REPORTED CROSS LENDING BETWEEN MFIs CROSS LENDING BETWEEN MFIs (%) A 39, % B 32, % C 20, % TOTAL 92, % MFI LOANS REPORTED CROSS LENDING W/ REGULATED ENTITIES CROSS LENDING W/ REGULATED ENTITIES (%) A 39,883 B 32,508 C 20,119 TOTAL 92,510 7,884 8,573 4,451 20, % 26.37% 22.12% 22.60% 24

24 Sometimes, awareness is everything! 25

25 Subscription fee, annual fees; cost of inquiries is perceived as very expensive by MFIs. Inquiries made trough leased lines only (no inquiries trough the Internet). To report data MFIs have to buy an expensive software license (validation tool) and use the leased line to submit the data, as well. Minimum batch queries accepted is 1,000. Standard credit reports of 9-12 pages The network negotiated more affordable conditions with the credit bureau. The network hired a leased line and started reporting and inquiring for the MFIs. Later, created a sort of bridge that allows MFIs to inquire through the Internet directly. The Network bought a software license and started reporting data for each MFI. Later, the network negotiated a 92% discount with the software vendor and started training MFIs to report by themselves The credit bureau presented alternate ways to access it s database. The credit bureau decided to lower the minimum number of batch queries to 300 The Network designed a more targeted one-page credit report 26

26 Hiring and training of additional staff to improve the technical and commercial capacity of the Network Distribution to the Network members a policy for inserting the use of credit reports in the credit risk assessment process. Put in place a policy and a procedure to insert the use of credit reports in the credit risk assessment process. Subscription of a code of conduct for all participating MFIs Development of a database of contacts of the Network members Marketing visits and follow-up for recruiting more MFIs Coordination meetings between the Network and the credit bureau Training meetings for data reporting and credit report interpretation for newcomer MFIs 27 27

27 % of credit bureaus receiving information from each source 100% 80% 94% 75% 68% 86% 82% Over 50% of emerging market bureaus reportedly receive information from MFIs Just over a quarter of these bureaus receive information on individuals in MFI lending groups Data quality remains an issue with respect to data provided by MFIs 60% 57% 52% 51% 52% 44% 44% 40% 23% 20% 0% Private Comm. Banks Public Development Credit Comm. Banks Unions/ Banks Coops Finance Credit Card Firms Retailers Corp. Issuers providing loans/trade Creditors Utilities Providers Credit Microfinance Bureaus Institutions Public Agencies courts) Source: Doing Business

28 High Income Traditional Credit Bureau Microfinance Focused Credit Bureau Middle Income Low Income 29

29 Products, services Credit reports: 1-2 pages Credit reports for group-lending : Basic information of 3-20 people in one report SMS-based credit reports Alerts Loan Portfolio analysis Friendly-user system; must perform well with poor Internet band-width Data Providers All types of lenders Utilities (gas, electricity, water, telephone) Judicial Courts Multi-Level marketing companies 30

30 You remain the Operations Manager at MicroMicro, now that you are better versed in Microfinance Credit Reporting, would your findings been any different? How? MicroMicro 31

31 Thank You 32