37 businesses with total scores ranging from the lowest to the highest 73.20 points
77.93 points. The branch's customer credit rating is different from VCB's regulations. The group of customers with a score from 77.2 -> 84.7 is rated at level A. Thus, some customers with a credit rating of A+ are only rated at level A for 26 customers. As for customers with a credit rating of A, they can be rated at level BBB according to VCB's regulations (The group of customers with a score from 69.6 - 77.1 is rated at level BBB).
Customers with TD BBB rating have 10 businesses with total scores ranging from the lowest 70.26 points to the highest 72.80 points. This rating is in accordance with VCB's regulations.
Customers with credit rating level BB have 07 enterprises with total score fluctuating at the lowest level of 64.55 points and the highest level of 65.47 points. This rating level is in accordance with VCB's regulations (Customer groups with scores from 62.0 - 69.5 are rated at BB).
There is 01 enterprise with a total score ranging from the lowest 60.72 points to the highest 60.72 points (1 enterprise). This rating is in accordance with VCB's regulations (Customers with scores from 54.4 to 61.9 are rated at level B).
Customers with CCC credit rating have 01 enterprise with total score ranging from lowest 58.69 points to highest 58.69 points. In accordance with VCB regulations (Customer group with score 46.8->54.3 is rated at CCC level)
Customers with credit rating level C have 01 enterprise with total score ranging from the lowest 46.26 points to the highest 46.26 points. In accordance with VCB's regulations (Customer groups with scores from 31.6 -39.1 are rated level C)
Customers with credit rating level D are not available (Customers with score below 31.6 are rated level D)
(2) Financial information
* Description of the balance sheet of 115 enterprises borrowing capital at VCB branch. Of the 115 enterprises, 92 enterprises have balance sheets, and many indicators have very small values, no financial reserve fund, negative equity, ... the quality of information on the report is problematic (appendix table 3.7). There are 92 enterprises with complete financial statements.
* Description of the Business Performance Report of 115 Enterprises . Based on the Business Performance Report of 115 Enterprises, there are 91 Enterprises that have sufficient Business Performance Reports submitted to the bank. So there are about more than 10 Enterprises that do not have financial reports, but credit officers still appraise and rate customer credit. (Appendix Table 3.8, Table 3.10 and Table 3.11)
Indicators used for analysis
- Financial indicators (according to model 6C): There are 81 enterprises with sufficient financial indicators according to model 6C (appendix table 3.9)
- Non-financial indicators: According to information on corporate customer operations of Joint Stock Commercial Bank for Foreign Trade of Vietnam - Da Nang branch, non-financial information is divided into 4 groups.
Group 1: includes indicators on financial capacity and business performance of the enterprise.
Group 2: includes information about customer status and management capacity. Group 3: includes credit information.
Group 4: Information on business development potential.
In fact, from 115 enterprises, the exploitation of non-financial information encountered some basic difficulties as follows:
1. Group 1 information is lacking and inaccurate, the main reason is that a large proportion of enterprises that are customers of VCB-Da Nang branch are newly established enterprises. Thus, the indicators reflecting the long-term status of enterprises are unpredictable.
2. Because non-financial indicators are assessed by credit officers, there is almost no difference in assessment for enterprises, many of which are not assessed.
3. A large number of businesses have not issued shares, so there is still too little information from the market.
Comment : These difficulties lead to the use of non-financial information to evaluate corporate customers being incomplete and inaccurate.
* Select variables for the model
- Determine business ranking criteria (dependent variable)
+ Joint Stock Commercial Bank for Foreign Trade of Vietnam - Da Nang branch has ranked the enterprise according to the general ranking AAA - D. This ranking is based on 2 groups of indicators: total financial score and total non-financial score.
Enterprises rated from A to AAA are enterprises that have the ability to borrow and repay loans according to credit contracts.
Enterprises rated from B to BBB are enterprises that need to consider their ability to repay loans according to credit contracts.
Enterprises ranked from D to CCC are enterprises facing difficulties in production and business and are unable to repay loans according to credit contracts.
Using this result, dependent variables can be created that represent the credit rating of the business.
+ It is also possible to use the variables short-term liquidity and quick payment ability as dependent variables in the above model. Because these variables directly indicate the ability to pay debts of the enterprise.
- Factors affecting credit rating (independent variables)
Factors to determine the size of an enterprise: Currently at VCB - Da Nang branch, the size of an enterprise is determined based on the following criteria: form of ownership, capital scale and industry of production and business... Financial factors; Non-financial factors.
The author builds a model to analyze the impact of factors on the credit rating of corporate customers at the Joint Stock Commercial Bank for Foreign Trade of Vietnam - Da Nang branch. According to the classification of VCB-DN, enterprises rated A or higher have no credit risk (can be lent immediately), the remaining enterprises need to be considered when deciding to grant credit.
DF variable - Debt repayment capacity: 1 - Good debt repayment capacity; 0 - Poor debt repayment capacity.
Factors include: 22 indicators according to model 6c and some other non-financial indicators.
Table 3.1: List of independent variables
STT
Variable type | List of independent variables | |
1 | TTngan | Current Ratio |
2 | TTnhanh | Quick Ratio |
3 | Kythu | Average collection period |
4 | vqts | Asset turnover ratio |
5 | vqtk | Inventory turnover ratio |
6 | vqthu | Receivables turnover ratio |
7 | KNTL | Interest Coverage Ratio |
8 | tsno | Debt ratio |
9 | roll | ROA |
10 | roe | ROE |
11 | hsl_dt | Return on sales |
12 | donbay | Financial leverage ratio |
13 | a41a | Manufacturing and business industry |
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14
a42a | Size of the business | |
15 | a43a | Type of ownership |
16 | Var2.2 | Owner's capacity |
17 | Var2.15 | Customer's debt repayment status according to schedule after adjustment |
18 | var2.23 | Industry outlook at the time of assessment |
19 | Var2.31 | Stability of the output market |
20 | var2.35 | Enterprise reputation in the market |
21 | Var2.38 | Business development prospects according to CBTD's assessment |
22 | var2.41 | Business location advantage |
Of the 22 indicators above, there are 10 non-financial indicators and 12 financial indicators of corporate customers. This selection is based on the 6C model.
*Testing several credit rating models
a. Layered model
- Model: The classification model can be used to divide enterprises according to a number of criteria. This division is based on the similarity of enterprises as shown by these criteria. People use this model with the main idea that enterprises with similar characteristics will have similar credit behavior.
- Estimate: The following model is used to divide enterprises into 3 classes with the hope that each class will have different characteristics in terms of ability to repay credits.
- Model estimation results: among 81 enterprises with sufficient information on the above variables, most enterprises are ranked from A to AAA in group 3, enterprises from B to BBB are in group 2 according to the current ranking method of the bank.
Similarly, 55 enterprises in group A-AAA are classified as having good payment ability, in addition, 21 enterprises in other groups are also classified in this category. On the contrary, 4 enterprises in group A-AAA are not classified as having good payment ability. (See appendix table 3.13)
- Comment : The classification model in this case only ensures the classification ability corresponding to VCB's TD rating results of about 70%.
b. Logistic model
- Model: Use logistic model with DF as dependent variable and all other variables as independent variables.
- Estimation: Directly estimating this model with 22 independent variables, we have the following results (appendix table 3.14 and table 3.15)
+ If the current rating results of the bank are considered accurate, the estimated results have an accuracy level of 90%, in which enterprises with good payment ability have an accuracy level of 94.9%, similarly, enterprises with poor payment ability have an accuracy level of 77.3%. Thus, this model evaluates good payment ability more accurately than poor payment ability.
+ However, this estimation result may also show that for some enterprises, the current ranking results need to be further evaluated.
According to Appendix Table 10, we can see that there are many independent variables that do not clearly affect the solvency of the enterprise. This model may encounter multicollinearity (information of the variables overlaps, and the independent impact on the dependent variable cannot be separated).
Table 3.2: Regression results (1) after removing variables
Variables in the Equation
B | SE | Wald | df | Sig. | Exp(B) | |
a42a | 1.212 | .665 | 3.324 | 1 | .068 | 3.360770 |
TTngan | 4.115 | 1,402 | 8,619 | 1 | .003 | 61.234698 |
vqts | .001 | .000 | 3,565 | 1 | .059 | 1.000511 |
vqtk | -.001 | .000 | 6,988 | 1 | .008 | .999108 |
roe | .021 | .007 | 9.203 | 1 | .002 | 1.021176 |
donbay | -.149 | .074 | 4,023 | 1 | .045 | .861980 |
Var2.15 | -10.338 | 3,787 | 7,452 | 1 | .006 | .000032 |
Var2.31 | 4,727 | 2,394 | 3,896 | 1 | .048 | 112.909301 |
Constant | 4,680 | 2,224 | 4,429 | 1 | .035 | 107.751063 |
This is the regression result from SPSS after using BackWard Wald variable elimination procedure. The remaining variables in the regression are independent of each other, the B coefficients measure the impact of the independent variables on the solvency of the enterprise.
+ Enterprise size : The larger the enterprise size, the higher the enterprise's ability to repay debt. This is completely true because the larger the owner's equity, the stronger the ability to be financially autonomous. This is a factor that affects the enterprise's credit rating at commercial banks.
+ Short-term solvency ratio
This ratio shows how many dong of short-term assets can be mobilized immediately to pay each dong of short-term debt of the company. When this ratio decreases, it shows that the ability to pay is reduced and is also a warning sign of upcoming financial difficulties. If this ratio increases, it means that the company is always ready to pay.
debt payment. However, if this ratio is too high, it will lead to low capital efficiency such as: having a lot of idle cash, bad debt, poor quality inventory. This is a factor that affects the payment ability of customers and the credit rating of the enterprise.
+ Asset turnover ratio: This indicator shows how much revenue one dong of an enterprise's assets can generate. Through analyzing this indicator, commercial banks evaluate how much revenue the enterprise's existing assets can generate from business, which is the basis for evaluating the enterprise's ability to repay debt in the future. Thereby, evaluating the efficiency of using borrowed capital in the enterprise's business activities is enough to pay interest and principal to the bank when due. The higher the value of this indicator is over 1, the better, which is a factor that strongly affects the debt repayment ability of customers and the ranking results of each enterprise.
+ Inventory turnover ratio
Inventory turnover reflects the relationship between inventory and cost of goods sold in a period. This indicator shows how many times the inventory is rotated on average in a period to generate revenue. If the inventory level is not managed effectively, the storage costs will increase, and this cost will be passed on to customers, causing the selling price to increase. Affecting the business's product sales revenue. If this ratio is too high, sales revenue will be lost because there is nothing to sell. If the inventory ratio is too low, the costs related to inventory will increase. The number of inventory turnovers varies significantly in the manufacturing and business sectors. Therefore, when evaluating the debt repayment ability of enterprises, commercial banks also consider this indicator and it is also a factor affecting the credit rating of enterprises. Here we see that the low inventory turnover ratio reaches a value of 0.999<1.
+ ROE : is an index measuring the level of profit achieved on the capital contributed by shareholders. This index must reach a minimum of 15%. The higher the ROE of a company, the more effective the company's use of capital is, and the higher the company's stock price on the stock exchange. A decline in ROE is evidence that the company's investment has brought about a lower ROE than before. The higher this ratio is, the more effective the business is in using borrowed capital, which has amplified the after-tax profit earned on 1 dong of equity capital and vice versa. The higher the ROE index of a business, the higher the ability to repay debt and the higher the creditworthiness at commercial banks.
+ TC leverage ratio : Measures the relationship between assets and equity.
If the amount of finance from debt is large, the risk is greater and the ability to repay the debt of the enterprise is greatly affected if the loan capital is not used effectively. This affects the creditworthiness of the enterprise at commercial banks.
+ The customer's debt repayment status according to the adjusted schedule : This is a factor that greatly affects the credit rating of the enterprise at the bank and reflects the customer's debt repayment ability. If the customer's debt repayment ability is on time, without extension with the commercial bank, the credit rating of the enterprise with the bank is good, but if the customer's debt repayment status is not in accordance with the commercial bank's debt repayment plan, the credit rating is low.
+ Stability of the output market: The business activities of enterprises depend greatly on the stability of the output market such as: the number of products, goods consumed, the consumption market is growing and expanding, contributing to increasing the revenue and profit of the enterprise, the ability to repay debts of customers increases and the source of loans of commercial banks increases. If the output market of the enterprise fluctuates a lot and is unstable, it will affect the ability to repay debts of customers and the creditworthiness of the enterprise at the time of assessment will decrease.
- Comments : From the results of model estimation (1), we have the following specific comments:
+ According to model 6C, the 22 independent variables mentioned above are all meaningful (more or less) in evaluating corporate customers. However, if using the estimated results of table 11, it may lead to inaccurate evaluation because 14/22 estimated regression coefficients are not statistically significant (at a significance level of 5%). According to the results in table 11, these 14 variables will be eliminated, information from those variables will be considered as not affecting the good payment ability of the enterprise. Thus, a model is needed to overcome these shortcomings.
c. Overcoming multicollinearity - principal component regression
Apply the estimation technique described in 1.2.5.2. to the above 22 variables.
Performing principal component analysis, we get the results (described in table 3.4).
- Testing the suitability of the ACP model: KMO test for the existence of overlapping information of independent variables shows that with this data set, the variables contain overlapping information. Therefore, when directly estimating model (1), multicollinearity will occur. On the other hand, principal component analysis is appropriate. Bartlett's test for the independence of variables also confirms the above results (information is available in table 3.3)
Table 3.3: Tests for the ACP model
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. | .656 | |
Bartlett's Test of Sphericity | Approx. Chi-Square | 1752.342 |
df | 231 | |
Sig. | .000 | |
- With 8 main components, 77.23% of the differences between enterprises based on 22 indicators are preserved. This ratio can be increased by selecting more main components (see appendix table 3).
- Coefficients of variables: Appendix Table 13 gives the structural coefficients of 8 principal components from 22 original variables (the u vj in formula 1)
From table 13 combined with appendix table 4 we can calculate the coefficients β vj
in formula (2).
- Logistic regression of solvency by principal components
The regression results after removing variables on SPSS (after 5 iterations) we get the coefficients α in the following table:
Table 3.4: Regression estimation results (4)
B | SE | df | Sig. | Exp(B) | ||
Step 5a | FAC1_2 | -.715 | .496 | 1 | .149 | .489 |
FAC2_2 | 19,025 | 5,725 | 1 | .001 | 1.831E8 | |
FAC5_2 | 5,263 | 1,888 | 1 | .005 | 192,991 | |
FAC7_2 | 1,252 | .519 | 1 | .016 | 3,498 | |
Constant | 1.201 | .612 | 1 | .050 | 3.324 |
Table 3.5: Classification results
VCB ranking results
Forecast | % | |||
0 | 1 | |||
DF | Poor debt repayment ability: 0 | 15 | 7 | 68.2 |
Good debt repayment ability:1 | 4 | 55 | 93.2 | |
General Rate | 86.4 | |||