The Application Of Data Mining On Marketing Of The Credit Card Customer

As the credit card industry is fast developing nowadays, the research of the market and customer replaces seeking the amount of the credit cards. Then data mining play an significant role in the management of the whole life cycle in the credit card industry. Logistic regression model and decision tree model are the most common technique in data mining. We can cluster the customer and predict the customer’s future action effectively by using the technique reasonable. Furthermore, whatever the customer auditing in card sending process, the customer promoting and maintenance in card using process or using card risk control, data mining effect a lot in all these processes.This article bases on customer database marketing, one of the most profit project in credit card industry, uses the real data from one credit card center in our country to study some applications of the data mining. The first is the introduction of the algorithm of the logistic regression model and decision tree model. Then we separately use logistic regression and decision tree to build the model scorecard by analysing the former customer’s act and attributes like age, sex and profession and predict the customer’s future action. This paper mainly research whether the customer will accept our promotion by phone. By the scorecard models, we can use different strategy to different customer so that not only rise the success rate of the database marketing but also save the cost. At last, we compare both the process and result of the model building to find the most proper situation we use the data mining.