Research Of Potential Credit Card Customers Identification In Commercial Banks

For the domestic banking, the sharply increasing credit card service will be a great source of bank profit. The marketing work to credit card customers also gets more and more recognition. As the marketing work face lots of customers, and the competition becomes more and more drastic, the data mine technology is put to use in credit card marketing field, and will be an important tool of supporting market analysis and improving marketing efficiency.The purpose of this thesis is mining potential customers of commercial bank by using data mine technology indicating direction of developing credit card marketing for banks. The research background of this paper is China Merchants Bank Guangdong Branch. The paper, at first, points out the difficulties of bank affair and brings forward the research meaning. Second, it researches the potential customer recognition theory in China, puts forward the basic methods of recognizing potential customers in commercial banks and the paper's frame. After that, it mines current credit card customers with SAS, finds out the factors influencing customers' using credit card. Then it calculates each proportion by using AHP, figures out every factor's proportion influencing customers' using credit card. In order to improve the hit ratio and efficiency of customer recognition, it bestows customer worthiness value system and customer stability system to get the evaluation of estimate of customer's current worthiness and potential worthiness and build up two-dimension customer's classification model. Then it uses this model to classify personal customers of bank and get 4 types of customers, after that, it filtrates the classified customers and tidy up potential valuable customer and valuable customer as customer recognition data source. At last, on the basis of previous analysis, it educes the factor having the biggest degree of association and methods of finding valuable customers and potential customers and find out potential credit card customers from them with data mine methods.