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Research And Application Of Data Mining In Commercial Banks In Crm

Posted on:2008-03-26Degree:MasterType:Thesis
Country:ChinaCandidate:S L ZhangFull Text:PDF
GTID:2208360245462027Subject:Software engineering
Abstract/Summary:PDF Full Text Request
With our nation entering into WTO and opening of financial market the Chinese banking will be surely facing drastic competition with foreign banks. What is more important, monopolization and government protection has been removed, which causes the China banks have no advantages any more. With the development of Internet Banking and Electronical Finance, there is no clear separate of areas thus the network advantage, which has been proud of by the China banks, is also vanishing. So it is the necessary that the Chinese commercial banks implying new management theory and the information technology that is Customer Relationship Management (CRM) and Data Mining (DM) technology.Customer Relationship Management is a system under which the customers'information resources, with the help of advanced computer technology and management theory, can be integrated and shared among all divisions of an enterprise. It can help the manager in decision-making and the company in providing more economic, convenient, and thoughtful products or services for the customers. Data mining and data warehouse technology are two powerful tools for making CRM more scientific and accurate.In this paper, by using the advanced ideas of CRM for reference and with the status quo of commercial banks being considered, attempts to build a web-based CRM system prototype which can realize the basic functions of CRM system. Also, this paper explores the combination of data mining technology and CRM. Then, on the foundation of further investigation of the decision tree algorithm, the Microsoft decision tree algorithm is introduced to categorize the customers by the different financial products that they have bought and the classification rule set is obtained. By this rule set, the enterprise can provide better service for its clients by matching the right information with the right customer. A summary is offered and some further research is suggested in the last part.
Keywords/Search Tags:Customer Relationship Management, Data Warehouse, Data Mining, Microsoft Decision Tree Algorithm
PDF Full Text Request
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