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Development of Credit Risk Model Based on Fuzzy Theory and Its Application for Credit Risk Management of Commercial Banks in China

机译:基于模糊理论的信用风险模型的发展及其对我国商业银行信用风险管理的应用

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Artificial intelligent techniques were successfully used in modeling of highly complex and non-linear phenomena such as the credit. This study developed the traditional credit risk model to evaluate the credit risk of the commercial banks based on the fuzzy theory. And then the membership functions for the model were established with the evaluating indexes which belong to the credit risk degree gather of the commercial banks. For the convenience, Principle Component Analysis was also used to reduce the factors which have diverse impact on the credit risk degree of the commercial bank. The results show that the new model developed in this study can be used to make a quantitative evaluation of the credit risk of the commercial banks. Especially, the case study shows that the new credit risk model has a good application for the commercial banks in China. The results indicate that the new credit risk model may give the commercial banks in China a new method for their risk management.
机译:人工智能技术成功地用于高度复杂和非线性现象的建模,如信用。本研究开发了传统的信用风险模式,以评估基于模糊理论的商业银行的信用风险。然后,该模型的成员函数是根据商业银行的信用风险学位聚集的评估指标建立。为方便起见,原理分量分析也用于减少对商业银行信用风险程度不同的影响。结果表明,本研究开发的新模型可用于对商业银行的信用风险进行定量评估。特别是,案例研究表明,新的信用风险模型对中国商业银行有良好应用。结果表明,新的信用风险模式可能会给中国商业银行为其风险管理提供新的方法。

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