基于平滑扩充原理的商业银行信用风险评级模型及实证

本文通过银行的资产质量方面、资本充足率方面、管控效能层面、盈利状态层面、流动性层面与社会敏感度层面等构建商业银行信用风险评价体系。根据平滑扩充原理模拟生成大样本数据,对评级得分进行扩充,进而根据扩充后的大样本数据划分银行的信用风险等级。解决了由于样本少、无法对信用等级合理划分的难题。通过实证分析可以了解到,本文得出的银行评级信息和标准普尔提供的评价结论存在共同的序关系状态。因此,可根据本模型对大多数未经过国际权威机构评级的银行进行风险评级。

The Credit Risk Rating Model of Commercial Bank Based on thePrinciple of Smooth Expansion and Empirical Study

The weights of the index for the six aspects, based on the commercial bank credit risk evaluation index system, including capital adequacy, asset quality, management, earnings, liquidity and social sensitivity, can be determined by the use of coefficient of variation. Based on the principle of smooth expansion, large sample data could be simulated and the rating score could be expanded. According to the credit risk rating of large sample data, the credit risk rating of banks could be divided. The innovations and features of this paper are as follows: First, we simulate the large sample data and expand the rating score according to the principle of smooth expansion, and then according to the credit risk rating we expand the original sample after 20 times to divide the bank’s credit risk rating. This solves the problem: the small sample can not be credit grading. Second, by the use of the nonparametric Mann-Whitney U method, the conclusion is obtained that large sample data with the original rating score data distribution is consistent at the 95% confidence level. Third, the empirical study shows that the sequence relation of bank rating is in accordance with Standard & Poor’s rating result. Therefore, this model can be used on credit rating by most of banks which have not been rated the international rating authorities.