An Empirical Study On The Probability Of Default For Commercial Bank Credit Card

With the improvement of national income and change of residents’s consumption concept, the credit card business has been developing rapidly in our country. The number of card, card issuer and transaction amount has been significantly improved. However, with the increase of credit card transaction amount, the overdue outstanding amount has been greatly increased. In order to maintain stable development of the credit card industry, our commercial banks need to pay high attention to it. On the other hand, in order to conform with international and improve the risk management level in China’s commercial banks, the CBRC issued some guidelines and demanded our commercial banks to implement the New Basel Capital Accord gradually. The internal rating method is the core content of the New Basel Capital Accord. Either primary or advanced method, commercial banks should estimate the probability of default by themselves. Taking into account the use test principle, most banks estimate the probability of default using score card way. However, the banks use the score card for customer application, rarely use behavior data. The paper analyzes a commercial bank’s credit card data and gives some suggestions. This paper consists of four parts:The first part of this paper introduces the necessity and significance of evaluating probability of default for commercial banks credit card.The second part of this paper includes the second chapter and the third chapter. The second chapter introduces the related theory of credit card and credit score. The third chapter introduces the technology about score card and model verification method.The third part of this paper uses SPSS to carry out the empirical research on a commercial bank’s credit card data. Candidate variables are derived from the overdue behavior, loan behavior, trading behavior, payment behavior, consumer behavior and cash behavior. In order to improve the accuracy of the model, the figures are divided into two categories according to the customer’s overdue status at the end of observation. The candidate variables are grouped by using decision tree method and calculate WOE. Build the prediction model of probability of default respectively for the two categories by using logistic regression method and get the risk factors of personal credit card customer default probability finally.The last part of this paper analyzes and draws conclusions according to the result of the empirical research. In order to help our commercial bank risk management, this paper argues that our financial institutions should strengthen the study of risk parameters and the construction of IT system.