Credit Bureaus in Microfinance

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
1

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

2

AGENDA




PERSPECTIVES

3

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
4

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

5

HOW IS CREDIT INFORMATION USED?

In pre- In credit In portfolio
selection underwriting management

 To sort out bad  To identify bad  To identify
borrowers up-front borrowers deterioration of
 To offer better existing borrowers
 To price risk
conditions to good accordingly  To avoid aggregation
borrowers of bad debt among a
 To use automated / number of financial
 To reduce the cost semi-automated institutions
of credit underwriting tools  To collect the most
like credit scoring risky debt first

6

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

7

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
8

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

9

BENEFITS OF SHARING NEGATIVE AND POSITIVE INFORMATION

REDUCTION OF DEFAULT RISK AT INCREASED ACCESS TO CREDIT AT
THE INSTITUTIONAL LEVEL THE CLIENT’S LEVEL
Percent decrease in default rate Percent of applicants who obtain a loan

3,35
74,8

12% decrease in 90% increase
default rate in access
1,9 39,8

Negative Negative & Negative Negative &
information positive information positive
only information only information

Simulated credit defaults assuming an acceptance Simulated credit availability assuming a target default
rate of 60% rate of 3%
10
Source: Barron and Staten (2000)


CREDIT BUREAUS AND SUSTAINABLE POVERTY ALLEVIATION

IMPROVEMENT OF
INITIAL SETTING UP A MFIs
FUNDING CREDIT BUREAU FINANCIAL MFIs’
VIABILITY SUBSCRIPTION TO CB

CB SELF-
REDUCED POVERTY FINANCING

REPAYMENT
SUSTAINABILITY
OF THE CREDIT
BUREAU
INCREASE IN THE INCREASE IN THE
PROPORTION OF TOTAL NUMBER OF
BENEFICIARIES WITH MICROLENDING
REPAYMENT CAPACITY BENEFICIARIES
Source: Développement de la première Centrale des
Risques sur Internet pour les Institutions de MF
11
au Bénin, PlaNet Finance

AGENDA




PERSPECTIVES

12

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.)

13

THE CASE FOR INTEGRATED CREDIT BUREAUS

THE IMPORTANCE OF SHARING INFORMATION ACROSS
SECTORS
Types of
Information “Positive “Negative
Sources of & Negative” Only”
Information
“Full” Lower predictiveness
High
(information shared by predictiveness (e.g. Australia, Brazil)
banks, retailers, NBFIs,
(e.g.
mobile operators)
US, UK, Italy, South
Africa)

“Fragmented” Lower predictiveness Lowest
(e.g. information (e.g. Poland, Czech predictiveness
shared among banks Republic) (e.g. Morocco, South
only or retail only) Korea)

Source: Microfinance and Credit Bureaus, Peer Stein (IFC)
14

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
15

AGENDA




PERSPECTIVES

16

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
17

Source: World Bank 2002
18

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

19

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

20

MAIN AREAS OF ACTION IN THE PROJECT

PROJECT ROADMAP MAIN CHALLENGES ENCOUNTERED
 Office set-up and equipment  Technology challenge: not all
 Design of the data base MFIs in Benin are equipped with
 Establishment of procedures the adequate technology
 Training of credit bureau‟s administrator (internet…)  necessity to provide
 Creation of the website relevant technology and diversify
 Training of MFI personnel the information channels
 Choice of legal statute and registration
of the statute  Data collection challenge: it took
 Maintenance of the website time to make sure that the MFIs
 Awareness campaigns to convince had a common vision on the
other MFIs on the advantages of information they need and the way
becoming a member of the credit to collect it
bureau
22

HOW THE BENIN CREDIT BUREAU WORKS

MFIs MFIs

 Monthly filling and actualization of 3 tools to access information
INFORMATION GRIDS listing the number of  Internet
overdue payments of more than 30 days.  CD-ROM
 PDA (Personal Digital Assistant)

Files are sent Transmission of the
to the CB information required

CREDIT BUREAU
Confidential information gathered on each borrower
 Centralization of the information  Personal information on each borrower
 Consistency check of the information collected  Occupation
 Information processing  Number of credits obtained
 Information storage in the CB database  Nature of outstanding credit

23

EARLY TANGIBLE RESULTS

LOAN OFFICERS
 Better knowledge of the
An average of 150 applicants enabling a better
inquiries per loan officer decision making
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

27

DECREASE IN REJECTED APPLICATIONS AFTER THE IMPLEMENTATION OF THE
CREDIT BUREAU

MFI Jan. Feb. Mar. Apr. Comments of MFIs

« Beneficiaries are more
PADME 2% 1% 0.5% 0.5%
disciplined »

FINADEV 6.8% 3% 1% 0% „‟

CFAD 5% 3% 1% 0% „‟

28

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

29

KEY LEARNINGS

 Microfinance credit bureaus are effective tools to prevent delinquency, even
when the budget allows only for the sharing of 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

30

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

31

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
32

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)

33

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

34

HOW THE MOROCCAN CREDIT BUREAU WORKS: ARCHITECTURE
Clients
Credit Bureau Server Database

Software: Software: MySQL 4.1
- Application server - Application server
TOMCAT 4.1 TOMCAT 4.1
- Application CB-CLIENT - Application CB-ADMIN
- FTP SERVER - FTP SERVER

35

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
36

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
37

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

38

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
National Federation of Consortium of member MFIs
management for the
Microcredit Associations (“Economic Interest Group”)
CB

Specialized private entity or
third party (Experian, etc.)

39

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

40

AGENDA




PERSPECTIVES

41

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

42

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

43

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

44

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

45


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

46

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

Scoring efficiency

40

35
Low Risk Medium Risk High Risk
# Good / # Bad clients

30

25

20

15

10

5

0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

47


 A scorecard was implemented in the MIS of the MFI
 The MFI also have an Excel tool for testing the model

48


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

49

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
50

CONCLUSION: KEY SUCCESS FACTORS

KEY SUCCESS FACTORS FOR MICRO CREDIT BUREAUS

 Ensure that the information is actively shared between all
involved institutions
 To foster the Credit Bureau‟s success, a law requiring its use by
all relevant players can be put in place
 To ensure coherency in policy and administration, a Credit Bureau
should have one single overseeing body

51

CONCLUSION: PLANET FINANCE CONTRIBUTIONS

Like in Benin or Morocco, the objective of PlaNet Finance is to be technical and
institutional advisor to the Credit Bureaus project teams.
Our philosophy is to build sustainable credit bureaus managed by local operators
using open-source technologies. Our credit bureau software has been designed
in order to be easily adapted. The technologies used are widely known.
PlaNet Finance carefully selects the local technical operator for the project
development and administration through a formal invitation to tender followed by a
transparent process of bid selection.
PlaNet Finance also ensures that MFIs are given sufficient support and training.
Implementing a credit bureau is a long process (over one year usually) but not
necessarily a very costly one. Most often, the major issues are not the technology
but the institutionnal framework. Once this solved, PlaNet Finance can lobby to
help gather the needed financial support from potential partners and donors.
52

Thanks for your attention.

To know more, feel free to contact PlaNet Finance:

mdutheil@planetfinance.org

www.planetfinance.org

53

Credit Bureaus in Microfinance

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