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An empirical study on P2P loan default prediction model

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DOI: 10.23977/ferm.2020.030102 | Downloads: 30 | Views: 1239

Author(s)

Yang Yang 1

Affiliation(s)

1 Department of Insurance and Economics, University of International Business and Economics, Beijing 100029, China

Corresponding Author

Yang Yang

ABSTRACT

With the increasing role of personal consumption loan business in economic life, the Internet financial industry has developed rapidly. Due to the lack of supervision and related laws, many irregularities and illegal acts are mixed among them. A large number of enterprises with the purpose of gathering funds are mixed among them. Under the banner of Internet finance, illegal actions to absorb public deposits are carried out. At the same time, due to the lack of supervision and related laws, many irregularities and illegal acts are mixed among them. Industry competition, guaranteed income and other irregularities are prevalent in the industry. Companies in the industry generally use funds for advertising and blindly expand their scale. The most important compliance management and internal wind control mechanism have been in a backward or even missing state for a long time, resulting in a large-scale decline and Thunderstorm in the industry, which has a huge negative impact on industry development and economic development. Under this background, this paper focuses on the internal risk control and studies the application of Logit Model in the auditing model of personal consumption loan. Firstly, starting from the logit model itself, this model is reasoned and introduced. Then, the auditing model of personal consumption loan is established by using logit model. Through the establishment and testing of the model, the model is further optimized and the model is beneficial to personal consumption loan is obtained. Suggestions and suggestions on the design and use of the model.

KEYWORDS

Logit Model; Consumption Loan; Audit Model; Confusion Matrix

CITE THIS PAPER

Yang Yang, An empirical study on P2P loan default prediction model. Financial Engineering and Risk Management (2020) 3: 14-22. DOI: http://dx.doi.org/10.23977/ferm.2020.030102.

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