Behavior Research To Private Customers Based On Data Mining Banks

Zhejiang’s economic situation has not improved significantly in the past two years. However, the quality of bank assets continues decreasing. Low credit enterprises seriously erode the bank profits which urgently enhance banks to improve the level of customer risk management.Currently, individual loan business and credit card business account for nearly 40% of the entire assets business. Banks face higher credit risk, market risk and operational risk. Organizations involve a wide range which impact on the overall asset quality. Traditional risk management methods base on conventional logic, often utilize afterwards management and relatively low technology, monitor the risk irregularly and lack of systematical manage, which can’t meet the increasingly rapid development of banking business. This article, based on the theory of data mining, after a large number of literature review, do unconscious behavior analysis to the private client on the above two kind of business. Data cleaning and transformation provide standardized data for data mining. Setting clustering and decision tree modeling through SPSS Modeler of IBM to deeply analysis customer behavior. The author tries to find out the factors forming risks, analysis of abnormal information from normal value, in order to form model to predict future risks and monitor monitor current risks.Finally, on the basis of the availability of data and the research on data mining model, the author provides behavior monitoring index of private customers. This article can be a reference to management departments to improve decision-making level, to offer data base when forming credit policy, and to provide scientific reference when setting business goals.