Evaluation of Financial Indicators in the Credit Scoring System of Asia Commercial Joint Stock Bank for Corporate Customers


Note : Information must be entered completely and accurately. If the information entered is incomplete, the system will report an error and not allow Submit. At that time, the credit officer needs to check again and supplement the customer information completely.

The credit officer re-enters the information and all non-financial information will be deleted, if the credit officer has previously entered complete information to score the customer.

Step 2: Score financial indicators


Liquidity indicators group

Determine the size of the enterprise based on Table 2.12 - Regulations on enterprise size (Appendix 18)

Target group

work

Target group

debt balance

Industry/Business size

Income indicator group



Total financial score

Figure 2.6 - Financial indicators scoring chart


(Source: Asia Commercial Joint Stock Bank, Corporate Customer Scoring)


The value and proportion of each indicator mainly depends on the economic sector and type of enterprise.

Total financial score =(score of each financial indicator) X (weight of that indicator)

In which, the input of financial information is entirely based on the financial reports provided by the Enterprise:

- Balance sheet


- Business performance report


- Cash flow statement


Figure 2.4 – Enter customer quantitative information


(Source: Asia Commercial Joint Stock Bank, Corporate Customer Scoring)


The required financial indicators have been standardized according to the financial reporting form of the Ministry of Finance (Circular 200/2014/TT-BTC or Decision No. 48/2006/QD-BTC for small and medium enterprises). In case the enterprise prepares financial reports according to the old form (Decision No. 15/2006/QD-BTC), the CBTD needs to perform a group of indicators of the same nature to match the indicators of the new financial reporting form.

Financial information will be assessed through a set of 07 financial indicators for very small scale and an increasing number of indicators for larger scale.

These indicators will be automatically calculated by the software through the entered value set and determine the score result. In case of incorrect or missing data, the credit scoring system will automatically warn.




Figure 2.5 – Error warning system


(Source: Asia Commercial Joint Stock Bank, Corporate Customer Scoring)


However, some financial indicators need to be calculated by credit officers themselves, and these indicators are used to score some non-financial indicators.



Figure 2.6 – Other financial information


(Source: Asia Commercial Joint Stock Bank, Corporate Customer Scoring)


Step 3: Score non-financial indicators


The value and proportion of each indicator mainly depends on the economic sector and type of enterprise.

Total non-financial score = (score of each non-financial indicator) X (weight of that indicator)


Industry/Business size



Support from shareholders, board of directors

action to action

Operational efficiency of the company

company

Ability to pay

debt/business plan

Reputation in relations with ACB and other

Other credit institutions

Stability of the business environment

industry risk



Total financial score


Figure 2.7 - Scoring chart for non-financial indicators


(Source: Asia Commercial Joint Stock Bank, Corporate Customer Scoring)


Step 4: Score collateral


Enter information about the value of collateral and the value of loans at ACB

The scoring results are based on


Table 2.13 - Collateral ranking table (Appendix 19)


Table 2.14 - Results of collateral rating scoring (Appendix 20)


Step 5: Summarize scores and customer ratings


KH score = Financial indicators score * Financial weight

+ Non-financial indicators score * Non-financial weight


2.4. Evaluation of financial indicators in the credit scoring system of Asia Commercial Joint Stock Bank for corporate customers

Section 2.3 has briefly introduced the internal scoring system currently applied at ACB Bank. This is a rating model consulted by Pricewaterhouse Coopers Vietnam Co., Ltd. However, whether the results of the scoring system truly reflect the actual business and financial performance and the creditworthiness of customers has not been verified. According to the system, the assessment and scoring of non-financial criteria is still subjective and depends on the appraisal level of CBTD as well as heavy business pressure, forcing units to try to adjust their customer ratings to be high in order to create conditions for customers to enjoy competitive interest rates. Therefore, the position of the Credit Re-evaluation department is to assess all loan applications and customers, with the task of assessing credit risks related to loans, including re-evaluating the ratings of customers so that the ratings reflect the most appropriate business performance, financial performance, and industry development orientation of the enterprise...

Therefore, the topic wishes to study more deeply the method of building a system, focusing on analyzing the set of financial indicators (the set of indicators reflects the objectivity of the rating enterprise) . At the same time, find out which indicators in the set of financial indicators of the scoring system have a great influence on the customer rating results so that it can be easier to re-evaluate the rating results from the units.

According to the scoring system, the business sector is divided into 7 main industries and 33 sub-industries. The statistics of the total outstanding debt ratio of the whole bank as of December 31, 2014 according to the 7 main industries are as follows:


Table 2.15 – Proportion of outstanding debt by economic sector


STT

ECONOMIC SECTOR

Industry weight

1

Agriculture, forestry and fishery

0.05%

2

Mining industry

0.05%

3

Heavy industrial production

10.75%

4

Build

19.25%

5

Commerce

49.70%

6

Service

11.97%

7

Light industrial production

8.23%

Total

100.00%

Maybe you are interested!

( Source: ACB Credit Department – ​​Hue Branch)

In the credit scoring system, the financial indicators are applied in general to different industries, the non-financial indicators are different depending on each industry. Therefore, the thesis only focuses on studying the financial indicators and uses the Binary Logistic regression model for evaluation.

2.4.1. Reasons for choosing the model


Firstly : Risk quantification models such as Z-score model and consumer credit score model have some points that are not suitable for commercial banks in Vietnam. Because these models are mainly researched in developed countries with complete credit scoring systems, as well as almost constant indicators that are not much affected by external factors such as changing financial market conditions.

Second : In Vietnam, there have been many research projects applying the Binary Logistic regression model to real life and they have been done very well.

Third : The Binary Logistic model is commonly used to predict the possibility of an event that we are interested in (the probability of occurrence) such as whether the borrower can repay the debt or whether to lend money or not.

2.4.2. Database and indicators used for evaluation


Using data from 7 quantitative indicators (most frequently appearing) to score the corporate credit of 50 enterprises currently having credit relations with ACB - Hue Branch. The thesis uses the following indicators for analysis: Current payment capacity, inventory turnover, receivable turnover, total liabilities/total assets, profit after tax/average equity, EBIT/Interest expense

2.4.3. Variable selection in the model


To make the model more accurate and practical, we need to include many indicators in the model such as Moody's, Fitch, Altman ratios. However, due to limited research data, it is very difficult to include variables such as cash flow ratios and interest-related ratios. On the other hand, statistical standards require the number of observations to be 4-5 times the number of input variables (Hosmer - Lemeshow requires 10 times the number of input variables), not to mention observations to re-test the model. When the number of variables is too large compared to the number of observations, statistical software cannot run Logit regression, so the thesis will shorten the number of variables as follows:

Dependent variable: Y is the debt repayment ability of the enterprise


Y = 0: No bad debt or high debt repayment ability.


Y =


Y = 1: Bad debt or low debt repayment ability.


Independent variable

Statistically through the collected data, these are the variables that appear frequently.



Table 2.16 – Table of symbols for financial indicators


STT

Symbol

Target

Expectation Sign

Meaning of expectation

1

D1

Business size: D1 = 0: If the business is small or very small. D1 = 1: If the business is large.

not small

-/+

Advantages of business scale

2

X1

Current payment capacity

+

Solvency ratio

3

X2

Inventory Turnover

+

Management efficiency

treasury

4

X3

Receivables Turnover

+

Collection efficiency

debt collection

5

X4

Total Liabilities/Total Assets

+

Debt structure, financial scale of the enterprise

career

7

X5

Profit after tax/Average equity

army

+

Rate of return

8

X6

EBIT/Interest Expense

+

Effective use

use of assets

Current solvency (X1):


This ratio indicates a company's ability to use short-term assets such as cash, inventory, or receivables to pay its short-term debts. The higher the ratio, the more likely the company will be able to pay its short-term debts.

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