A Comparison Study on the Era of Internet Finance China Construction of Credit Scoring System Model

  • Hongjun Zeng Business School, Guangxi University, Nanning, China
Keywords: Credit Scoring System, Random Forest, Discriminate Analysis, Logistic Regression, Comparison Study.


At present, China's Internet finance has flourished, showing a variety of business models and operating mechanisms. Through Internet technology, financial institutions can speed up business processing and bring users a better service experience. However, there are also problems such as credit risk and user fraud, and it is urgent to improve the level of risk control through credit scoring models. Because of this, this article uses the borrower data of a Chinese financial institution from January 2017 to June 2017 as the original data, and then uses the Spearman rank correlation test to screen out the variables with reliable explanatory power from the many variables of the sample data, and then Based on the variables selected, R 3.4.3 and SPSS 23.0 were used to construct a random forest model, discriminant analysis model, and logistic regression model. In general, different models perform differently under different sample characteristics, but the discriminant analysis has been better applicable. This paper compares the judgment accuracy of these three types of models and tries to establish a more effective financial credit scoring method, to solve the problem of constructing China's credit scoring system model under the current Internet financial background.


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How to Cite
Zeng, H. (2020). A Comparison Study on the Era of Internet Finance China Construction of Credit Scoring System Model. Bangladesh Journal of Multidisciplinary Scientific Research, 2(1), 1-22. https://doi.org/10.46281/bjmsr.v2i1.453
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