Application of Bayesian Network in Improving Customer Credit Precision

Gang Ma, Bin Li, Fangfang Yang
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引用次数: 0

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.
贝叶斯网络在提高客户信用精度中的应用
为了使CRM更有效,需要对客户进行分类,实现个性化服务,从而提高客户满意度和忠诚度,信用分析和评价是重要的一步。在传统的客户信用评估方法中,客户信用评估精度不足,使企业陷入两难境地。针对这一问题,本文提出利用数据挖掘技术建立贝叶斯网络模型,提高客户信用预测精度。该方法结合先验知识和后期信息,利用贝叶斯网络模型挖掘信用隐藏信息,实现了对客户信用的完美预测。企业可利用该预测结果来完成经营决策,为企业赢得更多的客户,增强竞争优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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