credit risk management: lending to small business

7/31/2019 Credit Risk Management: Lending to Small Business

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GENERIC SCORING MODEL SME

Since 2002. All Rights Reserved. Scorto Corporation.

Description of the "SME" generic scoring

model

and recommendations on how to use it


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EXECUTIVE SUMMARY

This document describes the "SME" generic scoring model and contains recommendations on how to use the

model.

Key features of the model:

The "SME" scoring model is specifically designed for the purpose of evaluating small and medium

businesses

The model directly links the credit score of the borrower to the corresponding value of the probability of

default. In its turn, the probability of default is one of the key parameters for the risk-based reservation and

pricing.

Target customer

The "SME" generic scoring model is oriented towards assessment of a vast category of would-be

borrowers: creditworthy enterprises whose age exceeds 6 months.

Credit risk ranges

This scoring model allows defining score ranges that have different values of credit risk:

Less than 136

points

137 to 211

points

212 to 265

points

266 to 493

points

494 to 571

points

More than 571

points

Segment Name High+ High Acceptable Acceptable+ Low Low+

Level of the PD in

the segment26% 24% 7.35% 4.31% 1.37% 0.23%


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Main limitations for using this model:

This model is not recommended for evaluating businesses whose age is 6 months or less. This model is not recommended for evaluating borrowers who take a loan to pay off mandatory payments.

This model is not recommended for evaluating businesses that have negative credit history (written-off

debts) as well as businesses, whose managers have negative credit histories.


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CONTENTS

1. KEY TERMS AND ASSUMPTIONS

1.1 WORKING DEFINITION OF SME

This document uses a definition of SME that extends the definition used in the Basel Committee requirements (see

International Convergence of Capital Measurement and Capital Standards A Revised Framework, Basel

Committee on Banking Supervision, June 2004, page 60 - paragraph 273.)

The actual size of the companies used in this model development ranged from those with revenues of less

than USD 1,000 000 to over USD 50,000 000.

1.2 TYPICAL LOAN TERMS, IN WHICH THIS SCORING MODEL CAN BE USED

This scoring model of evaluation is intended to be used for business-needs loans that are granted for 48 months.

The model considers both secured and unsecured loan application.

The size of the loan in a specific case is determined taking into account the borrowers ability to service debt

obligations as well as the cost and type of the anticipated security.

The classification of security types in descending order is represented below:

- Housing assets

- Commercial assets

- Moveable assets

- Stocks of materials and capital equipment

- Securities

- Untypical collateral (pieces of art, rare automobiles, brands, and so on)

1.3 DEFINITION OF DEFAULT BY BORROWER

Defaultis failure by the borrower to perform his/her payment obligations.

A typical indicator of default is a delinquent payment that has not been made for a specified period of time.

In the parameters of this generic scoring model, we use the following criterion of defining when the borrower enters

the state of default: a borrower is deemed as being in the state of default when one of the mandatory payments has

been delinquent for 90 days or more.

1.4 INDUSTRIAL MEMBERSHIP OF BORROWER

Data of enterprises with different industrial membership was used during the model development process.

In order to increase statistical significance, as well as ease of analysis, the following sub-groups of the industrial

membership characteristic were selected:


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1. Agriculture, mining, oil & gas extraction, manufacturing;

2. Wholesale and retail trade, eating and drinking places, repair services, motion pictures;

3. Utilities, transportation, real estate, hotels;

4. Printing & publishing, contractors, and other services.

An industrial membership indicator is not used in the direct calculation of a score rating. However, this

characteristic should be considered in analyzing financial indicators because their values are subject to general

trends that exist within a particular industry.


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2. ANALYSIS OF BORROWER FINANCIAL STATE

2.1 DATA

This SME generic scoring model is developed based upon data on credit activity of 2,400 SME enterprises.

The used data cover the period from 2005 to 2008.

In the process of creditworthiness analysis, the following borrower characteristics were used:

Company Description:

1. Name of the business borrower

2. Number of employees

3. Age of the business

Collateral, Loan to Value:

4. Desired loan amount

5. Collateral evaluation amount

6. Collateral type

7. Expected type of collateral use

Credit History:8. Credit history of the business

Cash Flow:

9. Average three-month turnover means amount

Financial Ratio Analysis:

10. Current assets

11. Current indebtedness

12. Net material assets

13. Depreciation costs

14. Total assets15. Total assets for last year

16. Stock of materials

17. Pre-tax profit

18. Other payments

19. Own assets of business in the project, for which the loan is granted

20. Total payments on existing indebtedness

21. Total interest payments on existing indebtedness

22. After-tax profit

23. Net Sales volume


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24. Last year Net Sales volume

Days Past Due:

25. Delinquency duration (days)

Data on the borrowers financial state should be represented in a single currency in the form of integers.

The model is currency independent because the financial state assessment is done with the financial indicators

representing absolute figures.


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2.2 FINANCIAL INDICATORS

2.2.1 Liquidity IndicatorsThe amount of liquidity the business needs to finance its operations provides a certain degree of protection for the

creditor. Liquidity includes: on the assets side - turnover means (turnover capital); on the liability side - short-term

debts.

Current Ratio

CR=CA/CD,

where: CA - (Current Assets) Turnover means

CD - (Current Debt) Short-term debt

This ratio reflects the ability of the business to pay off its short-term debt using the turnover means. If the

ration is too big, that means that the business keeps too many resources as liquid assets and does not use them

for business development, research and investment. This is a managerial fault. Normally, financial institutions have

a relatively higher share of liquid assets as compared to industrial enterprises.

Quick Ratio

QR=(CA-Inv)/CD,

where: Inv. = inventories.

Sometimes this ratio is called a litmus-paper ratio. It is similar to the current liquidity ratio and reflects the

ability of the company to pay off its short-term debt like the litmus paper in chemistry is used to find out whether a

liquid is an acid or an alkali. Inventory and material costs and future expenditures are excluded from the calculation

of the quick liquidity ratio, since of all other turnover means, they have the smallest liquidity.

Debt Service Ratio

Debt Service Ratio=EBIT/Interest and Principal on Debts,

where:EBIT means Earning before Interest and Taxes

The indicator demonstrates the degree, in which the revenue generated by the business covers its

obligations on servicing and repaying its existing debt.

2.2.2 Structure of Own and External Means

Autonomy Ratio is calculated as the ratio of the amount of own means (capital) to the total amount of the balance

(currency):

AuR = E/TA,

where: E (Equity) is the own capital

TA (Total Assets) is total assets or the currency of the balance

The ratio shows the share of own means in the total volume of resources available to the enterprise. The

bigger this share is, the more financially independent (autonomous) is the enterprise.

Coverage Ratio

C=(EBIT+AE)/(IE+OTP)

where:


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AE(Amortization Expenses) - is the expenditure on amortization

IE(Interest Expenses) - expenses on interest payments

OTP(Other Payments) - Other mandatory payments (leasing payments, principal payments and so on)The denominator of the ratio contains all regular payments by the enterprise that might influence its

creditworthiness, namely, interests on all loans, long-term loan payments and leasing payments.

Cash Flow Ratio

C=Turnover/Current Liabilities,

where: Turnover is the amount of monthly cash flows on the accounts of the enterprise,

Current Liabilities is the amount of current liabilities of the enterprise

High values of the ratio are indicative of low credit risk

2.2.3 Analysis of profitability of the enterprise

Net Profit Margin

NPM = NP/NS,

where: NP (Net Profit) - after-tax profit,

NS (Net Sales) net revenues from sales.

Net profit per sales unit reflects the amount of net profit from the production activity of the enterprise (after-

tax) per sales unit.

EBITDA (pre-tax revenue)

EBITDA= EBIT/

where: - Average Total Assets.

The higher the profitability of assets, the more effectively the management uses corporate resources. It is

important to use the average total assets value for the reporting period instead of the by-year-end value, since

profits are earned during the entire year, not just at a certain point in time. This ratio is useful for the analysis of

same-industry enterprises; however, it should not be used for comparing enterprises from different industries.


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2.2.4 Analysis of Business Activity of the Enterprise

Dynamics of Changes in Corporate Assets

Total Assets Growth= /

Growth of the enterprise's assets in combination with a sufficient level of its corporate assets is indicative of

a lower credit risk for the enterprise.

Dynamics of Changes in Corporate Sales

Net Sales Growth= NS/NS_Last Year>

Low values of this indicator mean higher risk, since the level of sales bears witness to gloomy outlook for

the enterprise. High values of this indicator may also mean higher risk, since a sharp increase in sales level is

indicative of the active growth of the enterprise and during the period of active growth the enterprise's

creditworthiness tends to be lower.


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3. METHODOLOGY FOR BORROWER CREDITWORTHINESS EVALUATION

The financial state of a borrower can be evaluated based upon the basic calculation or upon a combination of the

basic and detailed algorithms.

The following diagram illustrates the sequence of actions when selecting a way of evaluating the borrower's

creditworthiness:

Basic approach is preferred when information about the borrower is insufficient or collected in different periods of

time. If there are indicators confirming a high level of credit risk, the applicant can be assigned the worst credit

score possible.

Detailed approach can provide more complete, but at the same time more general assessment of credit risk.

The scorecard allows evaluating a combined contribution of all objective and subjective borrowers indicators.

However, this approach does not allow determining critical values of a small number of factors.


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3.1 MISSING DATA

If a number of borrower characteristics used in the process of evaluating its creditworthiness, then financial

indicators calculated with the help of such characteristics are assigned minimal values.

In other words, missing data (borrower's failure to provide such data) negatively impact the enterprise's credit

score.

Despite the ability to automatically handle missing data, this model is assumed to use the entire set of borrowers

characteristics. Moreover, the lack of information not only complicates the creditworthiness assessment but also

prevent further system maintenance and monitoring.

In this context, the following recommendations can be used when filling in the missing data:

- In case the required data is missing but, nevertheless, there is information about their possible values, those

values can be used for calculations.

- Also, in certain cases, the missing data can be replaced with the industry average values.

3.2 BASIC ALGORITHM OF CREDITWORTHINESS EVALUATION

The result of using the basic algorithm of creditworthiness evaluation is assigning the borrower to a credit risk

group. A credit risk group is a classification attribute of a credit product that defines the probability of the borrower

defaulting on its obligations to the Bank.

Low

The values of financial indicators show that the borrower's creditworthiness is high.

AcceptableThe values of financial indicators show that the borrower's creditworthiness is good However, there are negative

tendencies in the borrower's financial activity. Liquid collateral must be provided by borrowers in this group.

High

The values of financial indicators show that the borrower's creditworthiness is unsatisfactory; financial activity is not

stable. Credit risk is extremely high.

Defining risk groups through the values of the indicators

Indicator name Low Acceptable High

Loan Amount/Collateral Value More than 100% 50%-100% Less than 50%

Cash Flow Ratio More than 70% 20-70% Less than 20%

Current Ratio ... ... ...

Quick Ratio ... ... ...

Autonomy Ratio ... ... ...

Debt Service Ratio ... ... ...

Own Funds in Project/ Loan Amount ... ... ...

Debt Service Ratio ... ... ...


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Net Profit Margin Ratio ... ... ...

Days Past Due ... ... ...

The final risk group can be defined using the following three methods:

Classic

In this method the final risk group is defined as the worst by all values of the indicators. This method allows finding

even the slightest deviation in the financial indicators of the enterprise.

Average

In this method, the final risk group is defined in the following way:

1. A numeric value is assigned to each of the seven indicators depending on the risk assessment:

Risk Score

Low 10

Acceptable 5

High ...

2. The sum of scores by all the indicators defines the final numeric evaluation:

Score=Score1+...+Score7

3. The Score is used to define the borrower's risk class:

Score Risk

8,1-10 Low

... Acceptable

... High

This method allows getting a risk evaluation that adequately accounts for the values of all the indicators. At the

same time, a critical value of an individual indicator has no significant impact on the final score of the borrower.

Optimistic

In this method, the final risk is defined depending on the risk group obtained from each indicator.

Let us define that:

N(Low) number of indicators whose rating is defined as Low,N(Acceptable) number of indicators whose rating is defined as Acceptable,

N(High) number of indicators

Then the final rating is calculated as Rating=Max{N(Low), N(Acceptable), N(High)}

This method allows getting a credit risk evaluation that adequately accounts for the values of all the indicators. At

the same time, a great number of factors that have the critical value will be adequately represented in the final

rating.


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3.3 DETAILED ALGORITHM OF CREDITWORTHINESS EVALUATION - GENERALIZED SCORECARD

The detailed algorithm of creditworthiness evaluation is a scorecard, whose set of characteristics is extended as

compared to that used in the basic approach.

3.3.1 SCORECARD

The scorecard is developed on the basis of detailed evaluation and analysis of inherent characteristics of the target

group of the borrowers, which allows defining a set of characteristics for the evaluation of the creditworthiness of a

prospect borrower.

The set of characteristics consists of the following main groups:

Objective characteristics of the creditworthiness of an enterprise

Subjective characteristics of the creditworthiness of an enterprise

Objective characteristics of the creditworthiness of an enterprise

Characteristic Attribute Score

Quick Ratio

Less than 0.2 0

From 0.2 to 0.25 5

From 0.25 to 0.35 17

... ...

Cash Flow Ratio

Less than 0.2 0

From 0.2 to 0.4 4

... ...

Current Ratio ... ...

Autonomy Ratio ... ...

Coverage Ratio ... ...

Net Profit Margin ... ...

Debt Service Ratio ... ...

Credit History ... ...

Net Sales/Net Sales Last Year ... ...

Total Assets/Total Assets Last Year ... ...

EBITTA ... ...


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Subjective characteristics of the creditworthiness of an enterprise

Characteristic Attribute Score

Company Age

Less than 1 4

From 1 to 4 11

From 4 to 8 14

Number of Employees

Less than 5 11

From 5 to 25 17

Type of Collateral ... ...

Use of Collateral ... ...

3.3.2 CALCULATION OF THE FINAL SCORE

The score rating that is calculated as the sum of two values representing objective and subjective characteristics of

creditworthiness is used as the resulting evaluation of the borrower's creditworthiness.

SsubSobjS +=

Each constituent value is calculated in the similar manner in accordance with the following principle:

Suppose }{...,,1 NXX - is the list of objective (subjective) characteristics used to evaluate the borrower's probability

of default,k

ix is the set of attributes corresponding to ith characteristic, where

iKk ..1= , iK - number of attributes of the ith characteristic, Ni ..1= .

Let us usek

iS to denote the score value defined for the kth attribute of the ith characteristic in accordance with the

generic scoring model.

Within this system of notation, information of the borrower whose probability of default is to be evaluation is

expressed through the corresponding set attributes },...,,{**

2*

1

21Nk

N

kkxxx .

A score value is assigned to each attribute based on the scoring model },...,,{**

2*

1

21Nk

N

kkSSS

Finally, the scoring rating is the sum:

**2

*1 ...21

Nk

N

kkSSSS +++=

At the same time, an increase in credit rating values corresponds to an increase in the probability of a [positive

outcome of the loan transaction, or, equivalently, a decrease in the borrowers probability of default.


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3.3.3 CALCULATION OF PROBABILITY OF DEFAULT

The rating that has been obtained through the use of the score card allows calculating the borrower's probability of

default.

The following formula is used for the calculation:

732/)52(1 = SPD

3.4 RULES FOR CLASSIFICATION OF BORROWERS BY 5 RISK GROUPS BASED ON THEIR SCORE

RATING

The value of score rating obtained according to the current model allows selecting loan portfolio ranges with

different levels of credit risk. And credit risk can be considered homogeneous within each range.

At the same time, many potential problem borrowers are located at the lower end of the loan portfolio that allows

reducing the probability of default in general by adjusting the level of approval of loan applications in terms of score

rating.

The boundaries of the selected ranges can be altered further in the process of monitoring and maintenance of the

scoring system. The homogeneity of credit risk within the selected ranges with the concurrent difference of the

probability of default between them remains the criterion for developing risk ranges.

The following ranges are defined for the purpose of classification of SME borrowers:

Less than

136 points

137 to 211

points

212 to 265

points

266 to 493

points

494 to 571

points

More than

571 points

Segment Name High+ High Acceptable Acceptable+ Low Low+

Level of the PD

in the segment26% 24% 7.35% 4.31% 1.37% 0.23%

Risk Group "High+"

This group is represented by borrowers whose score rate is up to 136 points.

The score rate of borrowers in this group is extremely low, which means a critically high probability of significant

losses.


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Risk Group "High"

The score rate of borrowers in this group is within the range of 137-211 points.For borrowers in this group, the probability of default is closest to the critical value. The borrowers' financial activity

can be characterized as unstable.

Risk group "Acceptable"

The range for this risk group is 212-265 points.

Risk group "Acceptable+"

The score rate of borrowers in this group is within the range of 266-493 points.

Risk group "Low"

The score rate of borrowers in this group is within the range of 494-571 points.

Risk group "Low+"

This risk group contains borrowers whose score rating exceeds 571 points, that is, equals or exceeds 572 points.

The above-described method of credit portfolio segmentation meets the Basel II requirements.

3.5 RATING RATIO TABLE

The current model involves the use of both basic and detailed algorithms of credit assessment.

The rating is a result of applying the basic algorithm and offers the following classes of credit assessment to be

assigned:

Low

Acceptable

High

The rating is a result of applying the detailed algorithm and offers the following classes of credit assessment to

be assigned:

Low+

Low

Acceptable+

Acceptable

High

High+

In case the borrowers application does not contain missing data or separate critical values of characteristics, the

connection between the and ratings can be described by the following decision matrix:


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Rating A Low Acceptable High

Rating B Low+ Low Acceptable+ Acceptable High High+

Thus, the rating allows specifying the rating values.

3.6 REGULAR BORROWERS CREDITWORTHINESS RE-ASSESSMENT

The current model can be used not only in the process of making a decision about granting a loan but also to

monitor changes in borrowers creditworthiness in the loan servicing process. A standard period of monitoring

changes in borrowers creditworthiness supported by this model is 3 months.

First of all, monitoring of changes in creditworthiness affects the following indicators:

1. Number of employees

2. Desired loan amount (in case of initiation of the credit line size change by the customer)

3. Collateral evaluation amount

4. Collateral type

5. Expected type of collateral use

6. Credit history of the business

7. Average three-month turnover means amount

8. Net material assets9. Depreciation costs

10. Stock of materials

11. Other payments

12. Own assets of business in the project, for which the loan is granted

13. Total payments on existing indebtedness

14. Total interest payments on existing indebtedness

15. Delinquency duration (days)

3.7 RECOMMENDATIONS ON HOW TO USE THE MODEL

3.7.1 Credit policy rules

1. Scoring assessment of small and medium enterprises cannot be considered as complete without taking into

account the dynamics of changes in financial ratios describing the objective characteristics of creditworthiness.

Since the scope of such changes should be evaluated with the set of external economic conditions and regional

specifics, a scoring system should have an adequate mechanism of scoring assessment adaptation.

A set of credit policy rules that allow reducing (penalty) or increasing (bonus) borrowers scoring assessment,

depending on the specific values of the indicators, can be used as this mechanism.

The table 3,6,1.1 contains an example of credit policy rules that allow responding to the dynamics of change in

objective characteristics of borrowers creditworthiness:


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Table 3,6,1.1 Rules dynamics of financial indicators

Rule Adjustment

Cash flow1

credit risk management: lending to small business

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