Business Analysis in Modeling of Financial Risk

DOI

10.2991/assehr.k.211209.247How to use a DOI?

Keywords

clustering; RMF model; multicollinearity

Abstract

The bank’s main source of profit is loans, the money lent out by charging interest to make a profit, but with great risk of not being able to recover. In economic globalization, especially in the context of financial internationalization, loan risk control is always an important research topic for banks. In this paper, for the data set of bank loan risk control, we use four statistical analysis models to predict loan defaults: Logistic Regression, Random Forest, Neural Network, and XGB, respectively. Draw ROC curves of the four models and cluster the users. Meanwhile, the AUC values of the four models were calculated. Through simple comparison and analysis, we select the optimal method and probe into the effect and importance of the coefficients.

Copyright

© 2021 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Dirun Zhang
AU  - Xiangyi Shan
AU  - Siqi Li
PY  - 2021
DA  - 2021/12/15
TI  - Business Analysis in Modeling of Financial Risk
BT  - Proceedings of the 2021 3rd International Conference on Economic Management and Cultural Industry (ICEMCI 2021)
PB  - Atlantis Press
SP  - 1520
EP  - 1525
SN  - 2352-5428
UR  - https://doi.org/10.2991/assehr.k.211209.247
DO  - 10.2991/assehr.k.211209.247
ID  - Zhang2021
ER  -