摘要
为了开发一个中国邮政储蓄银行某分行的信贷风险管理系统,采用了数据挖掘技术。首先对数据挖掘和数据仓库技术的相关概念进行了介绍,对现有的信贷管理情况进行了分析,结合我国银行业的实际特点,得到了一个基于数据挖掘的信贷风险管理模型的设计和实现方法。在此基础上,通过在分类以前进行属性选择,不仅改善了分类器的总体性能,也降低了数据采集成本,可以提高银行信贷工作的效率。
In order to develop a loan risk management system for Binzhou Branch of Postal Savings Bank of China,the da-ta mining（DM）technology is applied. The relevant concepts of DM and data warehouse technology are introduced. The available circumstances existing in the credit information management is analyzed. In combination with the actual characteristics of Chi-nese banking industry,a loan risk management model based on DM was designed. By attributes selection before classification, the overall performance of the classifier was improved,and the data acquisition cost was reduced. As a result,the efficiency of the bank credit service was improved.
出处
《现代电子技术》
2014年第4期78-81,共4页
Modern Electronics Technique
关键词
数据挖掘
分类算法
决策树
信贷风险管理
data mining
classification algorithm
decision tree
loan risk management
