1
Credit Histories Bureau Risk Management,
Product Range, Cooperation Regulation.

• CJSC International Bureau of Credit Histories

2
RETAIL LOANS

• Auto loans
• Consumer goods loans
• Education loans
• Mortgage loans
• Credit Cards

3
RETAIL LENDING IS BOOMING

• GDP as of 01.01.2006 reached 400 Bn UAH.
  Forecasted GDP growth
• 2006 F 3
• 2007 F 5
• 2008 F 7
• 2009 F 9
• Aggregate Credit Portfolio of banks as of
  01.01.2006 reached 157 Bn UAH.
• 2006 F 35
• 2007 F 40
• 2008 F 40
• Growth of loans to individuals as of 01.01.2006
  reached 32 Bn UAH.
• 2006 F 80
• 2007 F 80
• 2008 F 90
• Mortgage financing market size as of 01.01.2006
  is 10 Bn UAH.
• 2006 F 50

4
RISKS

• 50-60 of the total population have never applied
  for loans
• Risk of default (including anticipated losses)
• Risk of underreceived profit (average rate of
  failures 30-40)

5
NBUs risk assessment methodology is Inefficient

• Following credit risk analysis methodology
  offered by NBU, a bank may only derive
  conclusions similar to the analogies below
• Analogies
• Only black or white clothes
• Very cheap or very expensive hotel
• Shoes sizes 35, 40 and 45 only
• Due to this inefficiency, good clients may be
  sifted out.

6
Parameters

• How many parameters to choose
• Initially, nobody knows which parameters are
  indeed significant.
• Excessive number of parameters may negatively
  affect perceived evaluation.
• multicollinearity
• Time of questionnaire filling out
• Too few parameters (less than 5) considerably
  impairs successful solution of objective.
• A quick validation procedure should exist for
  parameters (verification and internal control).
• Scoring enables accumulation of statistical data.
  But information thus received may be used for
  purposes other than borrowers creditworthiness
  assessment.

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CREDIT BUREAU, SCORING

• A standard solution is based on the Expected Loss
  Rate (ELR) calculated as a result of two
  variables Probability of Default (PD) and Loss
  Given Default (LGD)
• ELR PD LGD
• Conventional scoring systems classify clients by
  their default probability, beginning from those
  having the lowest score (with the highest
  likelihood of default) to the ones with highest
  score (with lowest probability of default)
• LGD scoring model adds to this rating new
  variables by means of similar classification of
  clients by their expected final loss rate in case
  of default.
• OPTIMAL RESULT MAY BE ACHIEVED ONLY WHERE THE
  PROBABILITY OF DEFAULT MODEL IS COMBINED WITH THE
  LOSS GIVEN DEFAULT MODEL

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Scoring of credit bureau
A SPECIFIC TYPE OF SCORING IS CALCULATED ON THE
BASIS OF HISTORICAL DATA, CONTAINED IN THE CREDIT
BUREAUS DATABASE. THIS IS THE MOST COMPREHENSIVE
SCORING MODEL BASED ON A HUGE VOLUME OF DATA

• Principally, there exist two ways of delivery of
  credit bureau scoring
• ON-LINE Risk assessment on the basis of answers
  to inquiries to credit bureau followed by a
  credit report
• GROUP OF REPORTS (OFF-LINE) Risk Monitoring
  services portfolio analysis solicitations
  previous reviews analysis

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Types of Users

• Absolute partnership Partners that deliver
  and receive both negative and positive data,
• Extended partnership Partners that submit
  only negative information and receive both
  negative and positive data,
• Partial partnership Partners that submit and
  receive only negative information.
• Data provider is a partner of bureau which only
  provides data.
• Database Registries are both public and private
  registries which accumulate documented
  information.

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Hook up Procedure

• Stage 1
• Closure of Service contract between a
  Partner/User and CJSC International Bureau of
  Credit Histories 3 days
• Stage 2
• Coordinate compatible technical formats, and
  rules and deadlines of information sharing with
  IBCH. If needed, do so in writing. Data
  collection, processing, update, transfer and
  storage procedures are subject to clause 4 of the
  IBCHs bylaws. 10 days
• Connection to the base and system in testing
  mode. If needed, preliminary analysis of a sample
  or entire database of the lender 7 days
• Fill out and send to IBCH a special form with
  names and contacts of Partner/Users employees
  designated to work with the Bureau. 1 day

Name Position/title Contact phone e-mail
1 Lenders representative assigned to work with CHB
2 Lenders administrator
3 Lenders operator
4 Operator -2
n Operator - n
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Hook up Procedure

• Log-in on the Bureaus website or request the
  Bureau directly to install the system and make
  steps in accordance with the Information System
  Connection Regulation 2 days
• Receive personal identification numbers (PIN)
  from IBCHs designated person 1 day
• Access system in testing mode 3 days
• Work through the mechanism of data shipment to
  the Bureau (10 of the data base at the most),
  send inquiries and receive reports. If needed,
  formulate recommendations to the IBCH
  administrator on additional agreed modules for
  integration with the system of borrowers
  assessment, adopted by the Partner/User 10 days
• Stage 3
• If needed, Lenders employees (administrator,
  operator) may go through a short-term customized
  training in IBCH 2 days
• Begin regular data transfer in secure mode.

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Rules and dates of data exchange with IBCH

• IBCH offers three options of data sharing (??
  - credit committee, ??? banking operational
  day)
• Option 1.
• Lenders headquarters
• Lenders subsidiaries
• Under this option, IBCH closes agreements both
  with lenders HQ and subsidiaries, as separate
  legal entities, and issues certificates to each.
  Both lenders HQ and its subsidiaries may make
  inquiries and receive reports in real time mode.
  At the end of each workday, the lender and its
  subsidiaries send new and/or updated data to IBCH.

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Scoring Workflow
BANK
Info on borrower
IBCH WEB
Info on borrower
Info on borrower
Data check Financial analysis Credit
Scoring Credit limit
Leasing Company
IBCH SERVER
Info on borrower
Credit Union
Decision report
Decision report
Decision report
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Sample Basic Credit Report