Credit Scoring of SME
Using Credit Information
Database
Satoshi Kuwahara
CRD Association, JapanJuly, 2015
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1. What is CRD…?
2. Background of CRD Establishment
3. Credit Bureau & Credit Database
4. Concrete Image of Practical Usage

2

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1. What is CRD…? (1/5)
I.

Data Collection (p.4)
Collecting anonymous data from CRD members

II.

Creating Database & Model building (p.7）
Creating database and Building CRD models based on the large database

III. Variety of services (p.8）
Providing CRD members with variety of services

IV. Maintenance for the quality of CRD scoring models (p.9-）
Creating the system that evaluated CRD scoring models objectively

Scoringmodels

Maintenance

Variety ofservices

CRD
Members
Credit Risk
Database (CRD)

Data3

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1. What is CRD…? (2/5)
I.

Data Collection

CRD Association collects financial data on SMEs from members --- credit
guarantee corporations throughout Japan, and government-affiliated or
private financial institutions.
【Membership Composition & Accumulated data】
Credit guarantee corporations

51Government-affiliatedfinancial institutions

3

Private financial institutions

116

Credit-rating agencies, etc.

4

TotalThe governmental institutions※ as of Apr 1, 2015

174
5(Unit: 1,000)

Number ofdebtor

Number offinancial
statements

Incorporated SMEs
(default information)

2,210(340)

16,644(2,365)

Sole-proprietor SMEs
(default information)

1,099(160)

4,519(657)※ ※ as of March 31, 2015

Please refer to the next page:(Reference) Collected data & Created Financial Indexes from database

4

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(Reference) Collected data & Created Financial
Indexes from database❶• Financial data (B/S, P/L)
Balance Sheet
AssetsLiabilities• Current assets―Cash and cash
equivalents―Inventories• Current liabilities―Short-term debt

• Fixed assets―Tangible fixed assets―Intangible assets―Investments• Deferred assets

Profit & Loss Statement
Sales
Cost of goods sold
Gross profit• Fixed liabilities―Long-term debt

OperatingOperatingexpenses
expenses• Salaries expense• Depreciation expense
・・・・・・・・

Shareholders’EquityOperating income• Capital stock

Non-operating income/expenseFinancial Indexes• Interest expense
・・・・・・・・• Capital-to-asset ratio• Degree of borrowing on lending

Income before provision for income taxes• Ratio of interest-bearing liabilities

Provision for income taxes• Ratio of current profits to assets

Net income・・・・・・・・

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(Reference) Collected data & Created FinancialIndexes from database❷• Non-financial data (Qualitative items)–(a) Owning or not owning real estate; (b) Successor or no successor; and(c) Birth year of CEO.

• Default data– (a) 3 months or more arrears; (b) de facto bankruptcy; (c) bankruptcy; and(d) subrogation (applicable for credit guarantee corporations).
– (e) substandard and (f) potentially bankruptcy were added as correspondence
to BaselⅡ since April 2003.
* Attributes (for consolidation purpose)(a) First Japanese character of company’s name; (b) Date of establishment; and (c) Postal code.

6All Rights Reserved. (c) CRD2015

1. What is CRD…? (3/5)
II. Creating Database & Model building• Collecting SME financial data are stored in anonymous form.
• The submitted data are cleansed and consolidated. These process
enable to create high quality database and we monitor the quality ofdata continuously.
• We create scoring models for members with high quality andincomparable big database. We validate scoring models in order tomaintain the quality of those.

Financialinformation

Probabilityof default
(PD)

Model

CRD database
Financial data on SMEs
throughout Japan

7

Inputs (financial indexes):••••

Capital-to-asset ratio
Degree of borrowing on lending
Ratio of interest-bearing liabilities……..

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1. What is CRD…? (4/5)
III. Variety of servicesi.

Scoring service【Credit Guarantee Fee Rate Classification】

Members can use CRD scoring models andevaluate credit risk of borrowers and potential
borrowers. Since April, 2006,
CRD models has been using to decideCredit Guarantee Fee Rate Classification in theCredit Insurance System.

ii.

(Unit: annual rate %)Sample data provision

Members can use random sampling data from CRD database.
— To complete insufficient data for creating members’ internal scoring model— To validate members’ internal scoring model— To develop financial products in new areaiii.

Statistical information provision

Member can use statistical information such as the financial indexes.
— To compare the financial statistics based on each member’s customers with those of CRD
database for improving the credit risk managementiv.

Management consulting support System（McSS)

Member can use consulting tool constructed of CRD scoring model and CRD data analysis.

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1. What is CRD…? (5/5)
IV. Maintenance for the quality of CRD scoring models(1) Model quality management guidelines
We established the guideline on the model development, model operation &validation and organized the Third-Party Evaluation Committee for CRD scoringmodels.
(2) Regular Validation & its Assessment• We validate CRD models annually in line with the guideline and the regulation under
the Small and Medium-sized Enterprise Credit Insurance Act and FSA notification.
—————

To check the transition of actual data as compared with the data which the current models are based on
To check Accuracy ratio (AR) of the models
To compare PD with actual default rate
To check the stability of the model
To check the explanatory ability of the variables to detect default•The Third-Party Evaluation Committee for CRD scoring models assesses the result ofvalidation.
(3) Disclosure of assessment by the Third-Party Evaluation Committee
Annual Report by Third-Party Evaluation Committee is delivered to the members andthe summary of the assessments are disclosed to public on CRD website.
9All Rights Reserved. (c) CRD2015

2. Background of CRD
Establishment (1/3)

 Financial Business belongs to an information industry.

InformationMoneyBorrowers
It brings obstacles
for finance toBorrowers.

Lenders

Asymmetric Information
problems easy to occur.

It brings heavy
monitoring costs tolenders.

• In financial and capital markets, information sharing system is well-developed as aninfrastructure.
• SMEs that can’t use such an infrastructure suffer from asymmetric information problemseriously.
• Previous resolution of the problems for SME financing is to utilize the land as collateral.

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2. Background of CRD
Establishment (2/3)

Year-on-year rate (%)
30.0
25.0
20.0
15.0
10.0
5.0
Residential0.0-5.0-10.0
Commercial area
-15.0
80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 10
Source: Ministry of Land, Infrastructure and Transport••• In the 80’s, the land prices rose drasticallyand the financial system relied heavily on
the land as collateral more and more.

• However, Collapse of bubble economy
had occurred.
• The excessive amount of collateral or
heavy burden of guarantee was required
for financing.

Lenders need to improve the quality of risk management and borrowers(SMEs) hope to getbetter access to finance.
Both of them hold an incentive for the introduction of more rigorous evaluation of credit risks.

To create credit risk information
CRD was founded in March 2001 as a membership organization to collect data on
SMEs led by SME Agency. The primary objective of establishing CRD was to promote
the streaming and efficiency of SME financing by assessing their businessconditions based on data and by measuring credit risks related to SME financing.

11All Rights Reserved. (c) CRD2015

2. Background of CRD
Establishment (3/3)••

To deal with the requirements of excessive collateral in SME financing (To cope with thecollapse of the financial system relied heavily on the collaterals)
To manage the requirements of sophisticated risk management corresponding to BaselⅡ

The Leading user conference was organized by SME Agency.

CRD management Council was founded in March,2001.
*CRD Management Council renamed itself CRD Association in April, 2005.

••

58members attended.
Scoring Model (CRD Model 1 ver.1) was released.

【Missions of CRD】a) Facilitating the fund provision to SMEs in Japanb) Improving the quality of risk management in financec) Managing the database in a fair manner

12All Rights Reserved. (c) CRD2015

3. Credit Bureau and Credit Database
There are two types of organization that deal with credit risk information.
❶ Credit information centers designed to collect the personally identifiable credit
information (PICI) and having individual information reference function (CreditBureaus)→Sharing borrowers’ ( or potential borrowers’) individual credit information as
materials for judging their creditworthinessPrimary driving force-----Bank supervision for reducing non-performing loan
❷ Credit information centers designed to collect anonymous financial informationand having no individual information reference function (Credit Database)→Showing an average borrowers in the group with same attributes and moreaccurate prediction of the credit risk based on a large databasePrimary driving force-----Mitigating the constraint on SME finance13

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(reference) Credit bureaus
vs Credit databases
Credit bureaus (Credit research company &Designated credit bureaus)

Credit databases

Information

Personally identifiable information---Information of individual borrowers

Anonymous information---An average borrower in the group with same
attributes (statistical information)

Discipline on the borrowers

DirectTo acquire good financial record(“reputationcollateral”)
To avoid being blacklisted

Indirect
To belong to higher credit rating group
To improve financial condition

Promoting competition infinancial market

Direct, Limited
To reduce information monopoly

Indirect, Broad
To reduce overestimated risk-premium by
improving predictability

Constraint come from privacy
problems

Tight constraints— Contents(depth) of information— Tight constraints affect the depth andlength of database— Preservation period— Accuracy of data
―Needs for correction of self-information

No constraints— It is comparatively easy to develop deep andrich database enabling more value-addservices.

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4.Concrete Image of Practical Usage（1/2）
Many of CRD members employ CRD scoring models for validating their own
scoring models.

High Own scoring (PD)

Low

Low

CRD scoring (PD)High

 coincidence ofevaluation
Low risk zone Different evaluation
CRD scoring – HighInternal scoring – Low

 Different evaluation
CRD scoring – Low
Internal scoring – High coincidence ofevaluation
High risk zone

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• Focus on thedifference• Specify thecause of thedifference

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4.Concrete Image of Practical Usage（2/2）
Some of CRD members develop their internal rating systems by employing CRD scoringmodels. First, they group customers into the categories in accordance with the degree of
estimated PD based on CRD scoring models. Then they develop their internal rating
systems taking other attributes such as qualitative items into account.
Scoringmodels

PDfinancialratingRange ofPDA1<0.42%

A2Rating

OtherAttributes

Number ofcustomers

Ratio

Defaultrate

A1326

2.2%

0.3%

<0.65%

A2

1,568

10.8%

0.5%

A3

<0.78%

A3

3,248

22.3%

0.6%

A4

<1.15%

A4

2,653

18.2%

0.8%

B5

<1.86%

B5

4,832

33.2%

1.6%

B6

<2.48%

B6

1,325

9.1%

2.3%

B7

224

1.5%

12.5%

C

159

1.1%

45.0%

D

98

0.7%

100.0%

E

134

0.9%

100.0%

Total

14,567100.0%

・・・

Check points:❶ Is there homogeneity of credit risk in the same rating?
❷ Is there distinction of credit risk between each rating?
❸ Is there extreme concentration of customers or ratio inparticular rating?

Members can construct their internal rating systems reflecting statistical prediction of PD andqualitative items they have weighed for loan decision making, which contributes to theimprovement of risk management.

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