Research of Credit Risk Assessment System and Model Based on Neural Network and Rough Set Theory

There are many issues to be resolved in commercial bank's credit risk management theory and its application. Then personal credit risk identification and the credit risk evaluation model become the important content in the commercial bank risk management system. This article proposes a personal credit risk evaluation model. It is based on Rough Set and Neural Network. The major disadvantage on the establishment of personal credit rating process is that there are a lot of subjective factors in it. This Model aimed to resolve this disadvantage makes use of the Rough set attribute reduction method in the establishment of credit risk evaluation index system. Then this article will give a more scientific and practical BP neural network modal. Neural network has the powerful non-linear processing and generalization capability. It could be solve the problem which people determine the weight factors and ensure the accuracy and objectivity of the evaluation results.