Title :
Application of Bayesian Network in Improving Customer Credit Precision
Author :
Gang Ma ; Bin Li ; Yang, Fangfang
Author_Institution :
Dongbei Univ. of Finance & Econ., Dalian, China
Abstract :
In order to make CRM more effectively, we need to classify the customer and to realize the personalized service, so we can promote the customer satisfaction and the loyalty, analyze and appraisal the credit is an important step. In the traditional method, the customer credit evaluation precision is insufficient, which causes the enterprise into a dilemma situation. In view of this problem, this article proposed using data mining technology Bayesian network model increases the customer credit forecast precision. This method union prior knowledge and latter information, using the Bayesian network model to mine the credit concealed information, which realizes perfect forecast for the customer credit. The enterprises can use this forecasting result to complete the operating decisions, wins more customers for the enterprise, enhance competitive advantage.
Keywords :
belief networks; customer satisfaction; data mining; finance; probability; Bayesian network; CRM; credit concealed information mining; customer credit forecast precision; customer loyalty; customer satisfaction; data mining technology; personalized service; Bayesian methods; Biological system modeling; Computational modeling; Data mining; Data models; Predictive models; Training;
Conference_Titel :
Management and Service Science (MASS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5325-2
Electronic_ISBN :
978-1-4244-5326-9
DOI :
10.1109/ICMSS.2010.5575663