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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开发及其在中国商业银行信用风险管理中的应用

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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:人工智能技术已成功用于建模高度复杂和非线性的现象,例如信用。本研究基于模糊理论,建立了传统的信用风险模型来评估商业银行的信用风险。然后建立了模型的隶属度函数,并建立了属于商业银行信用风险度集合的评估指标。为方便起见,还使用主成分分析来减少对商业银行信用风险程度产生不同影响的因素。结果表明,本研究开发的新模型可用于对商业银行信用风险进行定量评估。特别是,案例研究表明,新的信用风险模型在中国商业银行具有良好的应用前景。结果表明,新的信用风险模型可能为中国的商业银行提供一种新的风险管理方法。

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