%A CHENG Yan-qiu, XU Zhan-dong %T Credit Risk Evaluation of Small Enterprises Based on Revised ELECTRE III by Theil Index %0 Journal Article %D 2019 %J Chinese Journal of Management Science %R 10.16381/j.cnki.issn1003-207x.2019.10.003 %P 22-33 %V 27 %N 10 %U {http://www.zgglkx.com/CN/abstract/article_16429.shtml} %8 2019-10-20 %X One of the key tasks of credit risk evaluation is to determine the reasonable evaluation model. However, many existing credit risk evaluation models are complete compensatory methods. Those complete compensatory methods have a problem that high scores under certain evaluation indicators can fully compensate low scores under other evaluation indicators. Furthermore, in the credit loans, commercial bank will not grant loans to customer who's the specific indicator is too low and other indicators perform well. To fill in the above gap, a credit risk evaluation model for small enterprises is constructed based on ELECTRE III. This model can avoid the complete compensatory problem.
First of all, using the net credit score flow of the new loan customer to decide whether this new loan customer loans or not. This method can evaluate the credit risk of the new loan customer and make ELECTRE III has the ability of learning from history loan customers. Secondly, the Theil index can not only reflect income differences, but also break the differences into difference within groups and difference between groups. Then, by using the Theil index, the index weights are determined based on the idea that "the greater the influence on default is, the bigger the weight will be". Finally, the preference thresholds of ELECTRE III are determined based on Theil index within groups. And the indifference thresholds of ELECTRE III are determined based on Theil index of non-default samples;the veto thresholds of ELECTRE III are determined based on Theil index of default samples. The influences of different evaluation index on evaluation result can reflect through those thresholds.Also the subjective determination of three thresholds could be eliminated.
The constructed model has been verified using the samples of a Chinese national commercial bank. The empirical results show that the key inductors of affecting the credit risk of small enterprises are enterprise's credit extension of the past three years, loan default record of legal representative, the total amount of payment through our bank, and so on. Also, the indicators which have big differences between default and non default customers are found, such as cash ratio, the ratio of net assets to loans in the end of year, the age of the enterprise, and so on.
In conclusion, this research aims at establishing a credit risk evaluation model for small enterprises based on ELECTRE III and extending a new vision on small enterprises credit risk evaluation theory and models.