Application Of Data Mining In Customer Management Of Bank

With the arrival of the "big data" era, the data mining technology have beenwidely used in all walks of life, especially in commercial banks which have a mass ofbusiness data or user groups., along with series of measures in our country, such asinterest rate liberalization policy bias propulsion, rural financial market which wasocclusion relatively become more and more popular, the establishment of new typevillage banks around the country, set up a convenience service point, have greatlyincreased the competition of rural financial markets. While the focus of competition ischanging from the competition of financial products into superior customercompetition in rural financial market where financial product is seriouslyhomogeneity, more quality customers you have, more possibility you can win in thecompetition. How can we effectively use technical to increase our competitivenessbecome a big problem to be solved in the development process of rural financialinstitutions.Because of the rural commercial bank’s developmental delaying and backward ofcustomer service, there is no effective means to Identify quality customers in thesystem though they have a large number of customer data. The research work of thispaper will try to apply the data mining technology into rural commercial bankcustomer service while establishing the customer model. It used SQL SERVER2008database tools to do data mining analysis of the rural commercial bank customermodel, it used customer information and historical business flow data service withinthe system as the basis, it researched on how to apply the decision tree algorithm isapplied to areal customer analysis data, excavated implicit rules, quantified thespecific scoring models, and made adjustments to the model according applicationcase at the same time, finally it established customer model in line with the actualneeds. The whole research process according to customer information, businessinformation and other data business history flow data within the system, after datacollection, extraction, pretreatment, using data mining technology, successfullyestablished a customer analysis decision tree model of percentile. After adjustmentand objective method correction, the model can provide a certain amount of support inaspects of rural commercial bank customer analysis and customer service.