Application Of Data Mining In Bank PCRM

With the acceleration of the process of global economic integration and competition intensification, the traditional extensive management mode of production-centered, output and dimension based, has been replaced gradually by the intensive management model of customer-centered and service-based. Customer Relationship Management(Customer Relationship Management-CRM) has been concerned among enterprises.This article mainly elaborated the data mining technology in the Personal Customer Relationship Management System(PCRM system) of Agricultural Bank. Through PCRM system’s analytical study, we found that the system currently in use is also limited to simple statistics, summary, but the customer classification, customer acquisition, customer retention, cross-sellling, have not been carried out in-depth research and analysis. To solve the mentioned points, this article plans to use the data mining, such as decision tree, Bayesian classification, rough set and the connection rule, to realize the reconstruction of the PCRM. Concrete realization of the function modules are:the size of segments, evaluation of segmentation, product segmentation, attribute segmentation, trends, segmentation and channel segments.After system function transformation completed, the system can deliver partition and analysis towards ABC’s customer according to dimensions, products, customer attributes, classification and evaluation; can check all kinds of statistical reports to understand the overall situation of the institution’s clients; can support the extension of customer information, analysis and use, as well as the maintenance of customer functions; can provide convincing analysis of data for the business department.