Research On Data Mining Technology In Personal Financial Banking CRM

Under the current economic globalization, network realization, and the financial liberalization, banks are facing serious competition from not only the bank industry but also major foreign financial institutions. To maintain competition advantage, China's financial industry must rapidly change business strategies and concentrate on customer services. Therefore the establishment of the customer-concentric management information system is the inevitable choice under the new management thinking combined with the latest information technology developments. This article explores utilization of data mining technology and CRM to achieve the banks' customer relationship management. Based upon the data mining classification analysis theory, the connotation of the data mining, processes, and applications were discussed. The design of CRM system in bank personal financial services has been elaborated in this article.The thesis focuses on the decision-tree classification algorithm and application of decision-tree. Decision-tree is a classifier in the form of a tree structure with sample property as nodes and property values as branches. The ID3 algoritlim is the most influential algoritlim in building strategic tree models. In this article the classical ID3 algoritlim is applied to the bank customer credit classification. First phase is data preparation; the complete data sets are formed after taking operations on data extraction, data cleaning, and data dependence analysis and data transformation in the bank's database. Then apply classic ID3 algoritlim to build decision tree structure. Finally based upon the classification rules generated by the decision tree, classify banks customers into different groups and carry out proper target marketing for different groups to avoid risks and enhance credit quality service, which will develop the best strategy guide for bank loans business.