证券公司客户综合分析系统的设计与实现

介绍基于数据仓库与数据挖掘技术的证券公司客户综合分析系统的设计与实现,其中着重介绍了系统的设计原则、设计思想以及有证券特色的数据挖掘模型及其应用等重要内容。用k-Means聚类方法构建了客户偏好细分模型,将客户有效划分为8群;利用决策树及Logistic回归相结合构建了客户流失预警模型,结果表明该模型对客户流失捕获率有很大提升。

Design and Implementation of Securities Company Customer Analysis System

The purpose of this article is to introduce the design and implementation for Securities Company Customer Analysis System based on data mining technology, which focuses on system principles, design ideas, the securities characteristics data mining model, its application, and other important content. With the k-Means clustering method to build a customer preference segmentation model, the customers are effectively divided into eight groups. Using the Decision Tree Combining with the Logistic regression method to Construct the Customer Loss early-warning model is constructed. The results show that the rate of Customer Loss Capture significantly increases after implementing the customer loss early-warning model.