Based Data Mining Technology In Rural Commercial Bank In CRM System Design And Adoption

With the development and evolution of management idea in our financialindustry, the role of customers in the management is increasingly important.Meanwhile, the idea of customer relation management has already formed gradually.However, in operation and management of financial enterprises, customerconsciousness and service awareness of enterprises are still weak, particularly in ruralcommercial banks, which can’t form real customer consciousness and serviceawareness and are lack of deep excavation and analysis on customer data. In this way,the majority of customer information has been still in idle state until now. Financialinstitutions are distinct with industrial characteristics and business principles. Valueof customer information is not exploited.First of all, this task combines the idea of customer relation management andmodern information technology, so as to establish a platform that is based oncomputer network and regards customer relation management and maintenance asobjectives and realize a comprehensive and integrated management system on ruralcommercial banks’ customer relation management. Customer relation managementsystem of rural commercial banks adopts VS2010as the development tool. Thescripting language is JavaScript. Meanwhile, it considers C#as the developmentlanguage. Background database applies SQL SERVER2008database system, which isbased on ASP.NET MVC framework and combined with PLINQ technology anddecision tree algorithm, to realize basic functions for customer relation managementsystem of rural commercial banks, including customer basic information management,notification management, appraisal management and marketing management, etc. andmake customer relation management of rural commercial banks become reasonableand standardized.By introducing and comparing data mining technology, a mining method that isfit for solving problems concerning customer relation management of ruralcommercial banks is selected. Through specific data mining experiment, the paperexcavates business data of customer relation management, explains and evaluatesmining results, and assists rural commercial banks to establish advanced customerrelation management system, so as to excavate targeted customers, satisfy customerfinancial requirements, improve precision of customer management and increase customer loyalty. Ultimately, the paper proposes a model and implementation methodfor customer relation management analysis system of rural commercial banks basedon data mining, and comes up with beneficial understanding on customer relationmanagement business application of rural commercial banks, from the perspective ofdata mining. Correct implementation of system will make financial institutions mastercustomer dynamic conditions at anytime, subdivide market and provide “one-to-one”personalized service for customers.