基于数据挖掘的银行个人客户信用评价指标约简

Q. Yin, Ke Lu
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引用次数: 3

摘要

对银行个人客户进行信用评估是银行消除风险的重要手段。但是大多数研究中的银行客户信用评价指标体系过于复杂,难以应用。本文尝试基于数据挖掘方法,包括聚类方法和决策树方法,对银行客户的信用评价指标体系进行约简分析。本文构建了一个通用的银行客户信用评价指标体系。利用聚类方法分析了指标体系的合理性,并据此将指标体系从18个指标缩减为8个指标。通过决策树方法验证了该约简指标体系的有效性。简化后的信用评价指标体系效率更高,分析成本降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data mining based reduction on credit evaluation index of bank personal customer
Making a credit evaluation to bank personal customer is an essential way to eliminate the risk for banks. But most credit evaluation index systems of bank customers in most researches are over complicated and difficult to apply. The paper attempts to accomplish reduction analysis on credit evaluation index system of bank customer based on data mining method, including cluster method and decision tree method. In this paper, a common credit evaluation index system of bank customer is constructed. Moreover, the rationality of the index system is analyzed by clustering method, and according to which, the index system is reduced to 8 indexes from 18 indexes. Furthermore, the efficiency of the reduced index system is verified by decision tree method. The reduced credit evaluation index system is more efficient with the analysis cost declined.
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