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Applications Of Data Mining In Retail Banking CRM

Posted on:2014-11-25Degree:MasterType:Thesis
Country:ChinaCandidate:D D WeiFull Text:PDF
GTID:2268330428957349Subject:Applied statistics
Abstract/Summary:PDF Full Text Request
Customer Relationship Management(Customer Relationship Management, CRM) is a hot topic in marketing. As market competition intensifies, people become increasingly aware of the competition in the market is the enterprise competition for customers. This is even more important for banks. Today, domestic banks have come to realize that the customer is vital business resources, how to retain customers in the fierce competition, has become the key to success among the competition between banks.This article describes the specific details of CRM and the process and meaning of the data mining, as CRM analytics in retail banking an example, data mining methods will be applied to CRM analysis process in order to achieve a comprehensive grasp of the bank customers. This article use customer product preferences segmentation model, customer marketing response model, customer churn prediction model describes three aspects of data mining in CRM Analysis. Among them, the customer product preferences segmentation model using cluster analysis method, according to the customer’s transaction behavior segmenting customers in order to understand the customer’s overall characteristics of transactions; The decision tree algorithms are respectively applied to establish a marketing response model, customer churn early warning model, used to predict whether the customer will buy the high mobility financial products, whether the customer will be lost. Each model are introduced from the business objectives, data processing method, Model Assessment and so on. By the results analysis of the models, the customer segmentation model can distinguish the behavioral characteristics of the different customers, marketing response model, churn prediction model can correct response the actual situation of customers, the overall result is better.Finally, the deployment of the models and the models monitoring has been described, the modeling process in this article was summarized and make recommendations for changes of the models.
Keywords/Search Tags:customer relationship management, data mining, customersegmentation, loss warning, marketing response, monitoring
PDF Full Text Request
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