基于ROC决策树的民间借贷风险评估算法研究

Xiaohui Cui
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引用次数: 0

摘要

为了加强对民间贷款的风险控制,提出了一种基于多特征信息和风险敏感决策树的网络贷款项目风险评估技术。该方法首先建立贷款人在网络贷款系统中提交的客户信息中的信用状况,然后结合贷款人的历史贷款记录、个人特征、企业特征。采用ROC曲线下最大化和互信息最小的分析方法,选择与项目风险分析最相关且冗余最小的信息集。最后,运用完善的风险敏感决策树方法对贷款企业进行风险评估。测试结果表明,与现有方法相比,该方法在民间贷款风险评估中具有更好的性能。
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Research on Risk Evaluation Algorithm of Private Lending Based on ROC Decision Tree
In order to enhance the risk control of private loans, a risk assessment technology of network loan projects based on multi-feature information and a risk-sensitive decision tree is provided. In this method, the credit conditions of the lender in the customer information submitted in the online loan system is first established and then combined with the lender's historical loan records, personal characteristics, and enterprise characteristics. The analysis method with the maximization under the ROC curve and the minimum mutual information are used to select the information set most relevant to the project risk analysis and with the minimum redundancy. Finally, the risk evaluation of loan enterprises is carried out by using the perfect risk-sensitive decision tree method. The test result shows that this method has better performance in private loan risk assessment compared with the existing methods.
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