| Summary: | 碩士 === 中華大學 === 科技管理學系(所) === 96 === The middle and small business always play important roles in the track of our country’s development. Because of government policy to facilitate accommodation of middle and small business, the amount of bank loans to middle and small business appears to be increasing. Therefore, for the purpose to enhance bank asset quality, to improve business performance, and to decrease the possibility of middle and small business loan default, it is an important issue to set up a loan default predicting model for banking industry. The object of this research is the middle and small business loan customers of a commercial bank’s branches located in HsinChu and MiaoLio, first we adopt both the financial and non-financial factors to implement an empirical research , and by means of logistic regression to create a predicting model for middle and small business loan risk therewith. According to the result of this research, we find not only the related financial ratios of the default cases vary deeply from year to year, relatively, the related financial ratios of the normal cases are stable, but also some financial ratios show opposite result versus normal status. It reveals the possibility that the default loan customer dresses its financial statement. In terms of non-financial factors, the ratio of default varies from the elements of different industries、period of establishment、collateral、relationship with banks、 age of the person in charge, and whether the person in charge of uses the credit line of cash card or revolving line or not, moreover the difference of default ratio is quite apparent. Finally, this research makes use of the non-financial factors which have discriminating applicability to be the forecasting factors and creates a loan default precaution model for middle and small business thereby, the accurate ratio of the forecast is more than 85%. Hope the result of this research can help financial institutions to set up their middle and small business loan risk evaluation model and adopt some key reference factors therein.
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