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Data mining based reduction on credit evaluation index of bank personal customer

机译:基于银行个人客户信用评估指标的数据挖掘约简

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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.
机译:对银行个人客户进行信用评估是消除银行风险的必不可少的方法。但是,大多数研究中大多数银行客户的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的方法,包括聚类法和决策树法,对银行客户信用评价指标体系进行约简分析。本文构建了银行客户通用信用评价指标体系。此外,通过聚类分析指标体系的合理性,将指标体系从18个指标减少到8个。此外,通过决策树方法验证了降指标系统的效率。降低信用评价指标体系效率更高,分析成本下降。

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