Evaluation On Risk Of Consumption With Credit Card Based On BP Neural Network

Credit system is the foundation of the economic life in modern society. Along with the fierce competition of finance industry, bankcard becomes important earning way of commercial bank. To issuing bank, bankcard is a newer financial product which brings great profit. As the product of modern science and technology, bankcard plays great role in the business field of bank. It is the fountain of profit. As a derivative the bankcard is endowed with great risk. We all known, the credit risk is the prominent question which commercial banks face at present. So is credit card. It is affecting commercial banks' steady management. And it is also the intrinsic hidden danger that creates the systematic financial risk. The problem of credit risk has been the focus for the market economy countries all over the world and is the main obstacle to the development of the bankcard of our country.Therefore, in this case, accurately analyzing the commercial banks'risk and effectively guarding against the credit risk has much theoretical and practical significance. How to value a person's credit is an urgent problem in the course of the commercial banks' development.This thesis begins from introducing many kinds of theories about credit risk evaluating methods with reference of overseas documents. Then, the author compares the difference among the methods .By the way, the history of credit card is reviewed. At last, the author illustrates the credit evaluating model of BP neural network emphatically.There are five major parts in the text. At first, the author introduces the background of the topic, the research route and the whole framework. Secondly, the main theories of credit risk evaluating are introduced, including the definition, general situation of development and method running now in the test center of the simulating bank. Then, the author discusses the constructing process of BP neural network model for credit risk evaluation according to the real consumption data with credit card from the certain of commercial bank. Last but not the least, the author prospects the future of BP neural network model and points out the weakness of the article.Surveying the whole text, how to construct the BP neural network model for credit risk evaluating is emphasis. If you have some new idea about this topic, do not hesitate, welcome to write to me: weiliyuan@bigfoot.com. Thanks!...