Commercial Bank’s Management Research in Dynamic Lines of Credit Card
|School||Ocean University of China|
|Keywords||Dynamic limit Behavioral score BP neural network|
Since1985, China issued the first credit card of "Zhong Yin". The scale of credit card continues expanding. Amount of credit grows rapidly and bank’s income revealed gradually. At the same time, the bank will be faced with huge credit risk. The business of credit card develops at a high-speed in recent years. Announced by the People’s Bank of China, Credit card risk has begun to highlight though the visible data of indicators about the credit card-related risk. However, the bank does not has effective measures and means keep the speed of development.Presently the risk control of credit card industry in China mainly concentrates on the stage of distribution. The main reason is that the current credit card market centers on distribution, pays more attention to prior approval of credit card limit to determine the credit line. But after published the card, we pay little attention to the cardholder’s credit consumption situation, payment and credit status of the follow-up tracking. However, the task of risk control is not completed. We can’t let the credit card laissez-faire and die. On the contrary, the sustainable, scientific and comprehensive management on credit card accounts will help banks improve the line utilization of cardholder, keep customers, increase customers’ loyalty and prevent the loss of customers etc. Furthermore we can control the credit risk and increase the profitability of banks. On the basis of the analysis of credit card dynamic quota management, considering the development of China’s banking credit card and the change of economic environment factors, this article focus on the core stage of dynamic quota management of credit card to construct a more reasonable index system for credit card dynamic quota management. At the micro level, we hope to give customers a higher credit limit to promote the growth of credit assets and the increase of income, improve the market competitiveness of credit card, strength customer loyalty and reduce the credit limit which causes customer churn. Reasonable lower limit of credit card can reduce the potential bad debts preparation, cut down the "sleep cards" in credit cards and low excessive capital consumption of the credit. At the macro level, we can promote the development of bank card business, reduce the risk of banks and improve the competitiveness of the banking sector. Thus promote the development of banking.When evaluate index system, we select the BP neural network model through analyzing several of methods. On the basis of bank’s internal data, we feasibility analysis the index system by BP neural network model and achieve a good effect.At the beginning of transformation process from quantitative to qualitative in china’s commercial bank’s credit card business, we put forward a more effective management of the amount of credit card dynamic. We select the basic information of the cardholder, the bank’s internal situation and the macroeconomic variables to build a credit card index system of dynamic line management. Index system is more comprehensive and evaluation is more convincing compared with current index system which only selects indexes of customer behavior. When we evaluate the model, we do not divide the level of customers by scores, but we evaluate index system of credit card dynamic quota management by using BP neural network method which has highly parallel computing ability, self-study ability and fault tolerance ability, and it make the evaluation more scientific and more accurate.