Research Of Credit Rating Model Based On Neural Network

Personal credit system is the foundation of the social credit system. Good personal credit system is an effective guarantee of establishing the economic orders of socialistic market and taking precautions against financial risks. A complete personal credit system can greatly push the development of consumption credit. Enlarging internal demand and encouraging consumption are important measures to keep our country's national economy growing. It is right time to establish the personal credit system in order to stimulate the development of the consumption market. With the development of the credit economy, the importance of the Personal credit is evidence. How to value a person's credit, in order to develop the consumption loan and private finance operation, is an urgent problem in the course of the merchant banks' development, and also a question for discussion in our nation's credit management system. This thesis begins in analyzing theoretical problem of personal credit with reference of overseas experiences (Such as USA, Europe and other developing counties) in setting up personal credit system. Then, the writer summarizes the current situation and points out the problems and main restricting facts in personal credit system. After that, this thesis discusses the development of the personal credit assessment and summarizes the suggestions of strategies in building personal credit assessment system. Personal credit evaluation system is the core of the Personal credit system and important in the construction of the society's credit system. Taking advantage of the learning, nonlinear processing and error correcting abilities of neural network, a credit rating model based neural network is built according to the credit index of the enterprise and individual. It amends the defects of other methods. The model construction includes rating methods analyzing, index system and rating factors setting, sample data preprocessing and structure designing of neural network based on BP algorithm. The rating model supplies the foundation of the scientific management and correct decision for credit assessment organization and finance institutions.