Research On Risk Management Of C Bank Credit Card Project

In recent years,China’s bank credit card industry has maintained a good momentum of steady development,commercial banks’ card issuance and credit card loan scale has continued to grow,and the market influence is increasing,but influenced by a combination of factors such as the global economic situation,the new crown epidemic,and the increasing trend of strong regulation and strict supervision,the credit card industry has been plagued by fraud,cashing out and money laundering risks,and there is a gradual reduction of credit structure dividend.This paper introduces the challenges faced by the management of credit card projects in the banking industry,taking into account the characteristics of the times.This paper introduces the concepts related to credit card project risk management,compares and analyses the main risk identification methods such as neural network model,decision tree model,expert system method and Logistic regression model,raises questions on the current situation of credit card project risk management in Bank C,analyses the market environment,bank management and customer profile,and builds a credit card project risk evaluation index system around the age,gender,education and other characteristics of Bank C’s customers.The significant factors affect the default rate of customers are derived by establishing a Logistic regression model.This paper proposes effective measures to promote the risk control of Bank C’s credit card program,to further improve the level of refined management and digital operation,and to continuously strengthen its brand influence,so that the quality of Bank C’s credit card program operation can be continuously improved.At the same time,from the market environment,the bank itself and the customer dimension,it proposes countermeasures for the development of credit card project risk management,which will provide some reference value for the credit card projects of other commercial banks.