| With more and more abundant data of the bank,the mass data are described as "the data are abundant,but the information is lacking".As a result,the data collected in the large-scale database turned to "the data grave".Because the bank policy-maker lacks the tools which can extract the value information from mass data.Many important decisions of the bank are not based on data with rich information in the database,but on policy-maker's intuition.Data analysis through the Data Mining tool may discover the important data pattern.That transforms the bank data grave into "the gold bar" of knowledge.This dissertation focuses on how to realize bank credit based CRM system through the Data Mining technology.This dissertation is started from the theory of Data Mining Classification and CRM.And then it dissertates the meaning,course and application of Data's Mining Classification,and CRM's core thinking and type.The Data Mining Classification is described especially in this dissertation,and apply it in CRM customer's classifying of banking.In Data Mining Classification analysis,this dissertation describes the general decision trees algorithm, introduces and has compared several kind of typical decision tree algorithm.The commercial bank's a primary service is the loan.The bank has difficulty in discovering classified characteristic of the multitudinous loan applicants.Thus marketing strategy aiming at these customers lacks the foundation.The bank may use database or the data warehouse of the CRM system to classify customers.This dissertation uses the classified function of Data Mining to carry on the research of customer classification mainly using the ID3 algorithm. |
PDF Full Text Request