2023 Vol.6 Apr.N0.2

• Title: Credit Risk Assessment Method for Internet Finance based on Association decision algorithms
• Name: Mengdi Zhu
• Company: College of Finance and Trade,Zhengzhou Business University,GongYi 451200,China
• Abstract:

  At present, when using support vector machine classifier to evaluate Internet financial credit risk, there is no pretreatment of sample data, which leads to the shortcomings of low accuracy, high error rate and long execution time. This paper presents a credit risk assessment method for Internet finance based on association decision algorithm. This method analyses the shortcomings of the original index system of Internet credit risk assessment. Starting from the characteristics of Internet financial data, this paper chooses the data of a consumer finance company as the research object, preprocesses all sample data such as vacancy value processing, data cleaning, data standardization and sample grouping, and designs the index system of Internet financial credit risk assessment. By introducing the split information of attributes to correct the information gain of the data attributes of Internet financial credit samples, a credit risk assessment model of Internet finance based on association decision algorithm is constructed to measure the credit risk degree of each attribute, and the Internet financial credit risk is divided into five grades. The experimental results show that this method can effectively realize the efficient and accurate assessment of Internet financial credit risk, with the highest accuracy of 98%, and has more application value.

  
  

• Keyword: Association decision algorithm; Internet finance; Credit risk; assessment;
• DOI: 10.12250/jpciams2023090413
• Citation form: Mengdi Zhu.Credit Risk Assessment Method for Internet Finance based on Association decision algorithms [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.63-68

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