| Summary: | 碩士 === 朝陽科技大學 === 保險金融管理系碩士班 === 97 === Abstract
The small and medium-sized enterprises have been one of important economic lifelines and cornerstones of economic development in Taiwan. They have characteristics of flexible adjustment and access to the markets and their contributions to the economic growth are obvious to all from the point of view of the economic development in Taiwan in the past and now. Therefore, SME are the significant base for economic taking-off. However, The industry characteristics of the intransparency of financial statement and too small capital often cause a bottleneck for the demands of loans from the enterprise owners who are mired in the difficulties due to the consideration of credit risks by banks. The subjects of research were the enterprises in Taiwan. The parent body of samples was the credit loan application data by SME that a commercial bank transferred to the authorities for credit guarantees. The samples of NT dollar credit cases together with the financial situation of applicant enterprises that the researcher had obtained were total 308 accounts including default accounts and regular accounts. On the basis of the financial statement data for three years before the application, we assess whether the data could be the basis of loans for the bank that received the loan application. The research also analyzed the significance of the financial situation for recent three years before the ratification of loans between regular repaying interest accounts and default and collapsed accounts. Using the financial statement and the information about ratio of finance that were available in recent years in the loan applications by SMEs that had obtained credit guarantees from SME Credit Guarantee Fund, the research would determine whether the applicant enterprise would still face financial problems, that is, whether the company would default, collapse or sustainably and normally operate in future after ratification of loan that was credit guaranteed by the Fund. So the purposes of the research are as follows:
1.Based on the data provided by the bank about the SME that had applied credit loans and credit guarantee, it explored if there were significant effects of financial analysis ratio on the default risks of credit guarantee accounts.
2.Find out the factors that could be the quality of credit decision-policy for SME credit guarantees.
This research used Logistic Regression model to test the empirical results. It found that the five variables of the two-year current ratio, previous two-year total asset turnover ratio, previous three-year total asset turnover ratio, previous loan-asset ratio and credit ratio had significant differences in the current situation of operations. The forecast accuracy of the results of forecast classification through the regression model in the research on the closedowns of enterprises was 50.7% whereas the forecast accuracy on the normal case was 97.9%. The overall accuracy was 87.7% whereas the tested χ2=123.209（p=0.000<0.05）of overall goodness of fit of the model and reached the significance level. But the value of Hosmer-Lemeshow Test was 6.297 (p=.614>.05) and did not reach the significance level. That means the goodness of fit of the credit model of SME credit guarantee that was constructed on the bases of the five variables of the two-year current ratio, previous two-year total asset turnover ratio, previous three-year total asset turnover ratio, previous loan-asset ratio and credit ratio was ideal. Therefore, credit officers can use the model. Therefore, credit officers can use the model together with conditions of the applicant company to forecast in the shortest period the probability of collapse case or normal case in consideration of a loan.
This research can thus induct following credit model:
Z =4.551＋0.019× previous two-year current ratio－1.111× previous two-year total asset turnover ratio ＋0.797× previous three-year total asset turnover ratio－0.051× previous two-year loan-asset ratio－0.039× credit ratio
When a bank is considering loans to SMEs, it should not lose their strictness and carefulness that they should have and their credit policy should pay attention to both risks and profit. Therefore, at the time of seeking profit, if a bank can analyze the futurity of the case by regression model, we believe that they can avoid ruling out good cases and raise profit for the bank. Meanwhile, it can also screen out high risky cases and give consideration to risk control.
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