Oscar Madeddu - Lisbon - June 7, 2011

Wider access to credit, consumers’ empowerment,

lower over indebtedness, and reduced NPL

with credit reporting

Formalizing the “informals”

IFC Global Credit Bureau Program:

technical assistance in over 60 countries

2

• IFC is the private sector arm of the World Bank - started GCBP in 2004

• Technical assistance to regulators, governments, lenders. etc

• GCBP aiming at establishing credit reporting in developing countries

• No. of countries covered under Doing Business Report for credit reporting: 181.

• No. of credit bureaus created or significantly improved: 13 countries

• No. of credit bureau inquiries in those countries in 2008: 38.9 million.

• Volume of lending supported in these countries in 2008: $19 billion.

• Number of new laws/regulations drafted or contributed to drafting: 21.

• Number of seminars, conferences, outreach events: 70 events in 47 countries.

A worrying correlation!

Countries without

Private Credit Bureaus

are the same…

…where access to

credit is more difficult!

•Financials systems collapsed

•Deposits were frozen

•Depositors queuing outside the banks

•NBFIs totally liquidated

•16 banks out of 40 closed

•20% of GDP lost

•Debt/GDP ratio went from 81% to 156%

•Supervisor powerless and humiliated

•The consequences

•Around mid 90s capital inflows surged from US$200 mn per year to US$780 mn (5% of GDP).

•Liquidity glut provoked lax credit policies for households and enterprises

•Private credit increased 60% (or 30% of GDP compared to less than 15% in 1989-92)

•This led to a lending boom offered without proper risk assessment and information

•Moral hazard, excessive risk taking, financial corruption increased phenomenally

•No Private Credit Bureaus were present at the time

•In 1994 severe financial crisis hits in Ecuador

Our story starts in Ecuador during the 90s…

5 Fuente: SBS

Credit reporting results in Ecuador:7 years after PCBs establishment

“THE” issue: how to convince NR-MFIs to share data ?

•…the same clients had also other loans (green bars) with other lenders

•These lines of credit were even higher than MFI loans

•And clients were already using those loans (red bars)

•This was detected only because all the lenders shared with same PCB

0

100,000,000

200,000,000

300,000,000

400,000,000

500,000,000

2005 2006 2007 2008

MFI total loans outstanding (US$ mn)

Microcredit loans

0

100,000,000

200,000,000

300,000,000

400,000,000

500,000,000

600,000,000

700,000,000

800,000,000

900,000,000

2005 2006 2007 2008

MFI total loans outstanding + credit cards (US$ mn)

Microcredit loans Credit card utilized Credit card approved

•N-RMFIs believed they had exclusivity with their client, and that clients were loyal

•RFR compared their portfolios with the data contained in the Credit Bureau and…

•MORALE: it is crucial that MFIs share data with a PCB but not that MFI set up a separate PCB

•Big risks may be incurred while assessing new applicants without having a complete picture

The results?Project SERVIR (Jun. 05 to Oct. 06)

Number of microenterpreneur with credit

118.787

254.347

664.722718.919

528.329

407.310

59.507

0

100.000

200.000

300.000

400.000

500.000

600.000

700.000

800.000

02 03 04 05 06 07

41,53%

10,29% 11,20%8,71%

9,81%

0,00%

10,00%

20,00%

30,00%

40,00%

50,00%

2005 2006 2007

Índice de Cartera Vencida > 1 día (Proyecto SERVIR)Client Number: + 33,65%

Total portfolio: + 53%

Average loan: From $ 1,800 to 2,400

Portfolio At Risk: - 2%

Legal actions: - 0.4%

MFIs joining: 37 (initial objective 20)

Users number: from 7 to 135 (non-regulated)

Useful inquiries: 90% useful to approve credit

CLIENT NUMBER BY INSTITUTIONS %

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

100%

2002 2003 2004 2005 2006 2007 2008

With more than 5

institutions

With 4 institutions

With 3 institutions

With 2 institutions

With 1 institution

Before

project ServirAfter

project Servir

Special services for special users

BASIC MFI REPORT

Price for SMS report: $ 0.17 - $ 0.30, it varies

according to # of inquiries and records contributed

XXX YYY ZZZ

APR 08

DT: 323.760

DT: 201.150

I: 122.610

#ACRD: 5

DEFAULT: 0

+CATEGORY: A ABR 08

-CATEGORY: C JUN 07

SCA: ENA

Name of applicant

Date of the report

Total credit: Includes Regulated + Non Reg + Infocom

Direct Debt: Includes Regulated + Non Reg + Infocom

Indirect Debt: Includes Regulated + Non Reg + Infocom

# of credit inst.: Include Regulated + Non Reg + Infocom

Default credit

Best rating ever and date MMM YY

Worst rating ever and date MMM YY

Saving / check accounts: open / closed

FULL CREDIT REPORT

PCB

SMS

2. THE PROJECT:

• Project started by the local administration of region in the South of Italy

• Objective: increase credit access for non bankable applicants and/or without a

credit history ( “thin file or no file).

• The Water Company (public) has given historical data on water bills payments

• Sample window: data with bills payments from 2006 to 2008

• Population analyzed : 154,000 payers•112,000 with a credit history in the Private Credit Bureau

• 42,000 without credit history in the Private Credit Bureau

1. THE CHALLENGE:

• can a good payment track on water (and utilities) bills be considered as good as

credit data to build a credit history and scores for “unbankable”, informal

economy, Micro and SME, and individual customers without credit history?

The importance of “non-traditional data”

Case study (2010): WATER SCORE

• The answer is yes, the scoring model developed on water payment data allows a robust

risk assessment of those clients that pay their water bills regularly and punctually

Results?

• In particular those without credit history: 83% would be accepted.

SCORE Media % en

cl asseClasse

Bad Rate

odds

514.932 <= -- <=938.917 881.067 7.15% 1 12.27%

938 .917 < -- <=970.647 959.753 9.69% 2 4.15%

970.647 < -- <=977.784 976.107 16.10% 3 2.47%

977.784 < -- <=982.541 981.626 19.02% 4 1.78%

982.541 < -- <=985.418 984.718 10.26% 5 1.50%

985.418 < -- <=986.880 986.838 30.92% 6 1.11%

986.880 < -- <=990.488 988.987 6.85% 7 0.48%

In fact, among the

42,000 with no

credit history,

roughly 37,000

customers (83%

of them) can

become eligible

for credit, with a

good score

• If appropriately fine tuned the model can easily be extended to other utilities / or municipalities

• In conclusion, a potential “good” customer that finds it difficult to access credit through

traditional channels and traditional data could vastly benefit from alternative data utilization

Thank you!

Oscar Madeddu

omadeddu@ifc.org

PROBLEMS SOLUTIONS

MFI mistrusted information sharing

(claimed that competitors may take

customers away!!!!)

MFI s trained on PCB legislation that allowed access to PCBs only with reciprocity, only with client’s consent, for only a limited permissible purpose (granting credit, no marketing purposes, marketing lists, etc)

MFI low awareness of PCB benefits

Plus MFI believed their clients were

loyal!!!

Free portfolio analysis (30-70% of clients had loans with other lenders)

Free 6 months service trial

Subsequent special prices (based on matrix inquiries/records supplied)

Free portfolio management report (other MFIs’ inquiries, PAR, loyalty)

Lack of technology (MFI s operate with basic or old software, often simply Excel spreadsheets, and e-mail)

PCB created and installed in each MFI a technical device to automatically

extract information and transfer it to the PCB in the requested format.

PCB allocated 10% of revenues to finance a technology fund for users

Total pilot project costs for MFI/RFR US$ 180,000 (scalable, replicable)

Inadequate telecommunications Internet connections not always available, installed, or functioningAllowed initial different procedures to send information: diskette, CD.

Miscellaneous advantages for

participants to initial pilot

Potential availability new product ( e.g. visit scoring)Preferential rates for founders / usersPotential availability of new information (regulated MFIs, mobile tel.

retailers, banks, etc.)

“THE” issue: how to convince NR-MFIs to share data ?

Credit Applicants(information)

1

2

3

Regulated entities

Banks

Regulated entities

NBFI

Regulated entities

MFI

Non-regulated

commercial entities

Non-regulated

financial entities

Central Bank(no borrowers’ consent required)

Bank 1 Bank 3 NBFI MFI RETAILER TELCO

4

PCB 1 PCB 2 PCB 3 PCB 4

5 Bank 2

Sharing model: mandatory indirect information sharing

Borrowers’ consent

is required