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Academic Journal of Business & Management, 2021, 3(6); doi: 10.25236/AJBM.2021.030612.

Research on credit risk of commercial banks based on multiple logistic model

Author(s)

Jiexin Lu1, Yongzhen Tong2

Corresponding Author:
Jiexin Lu
Affiliation(s)

1School of Electronic Science and Engineering, Xiamen University, Xiamen, Fujian, 361005, China

2School of Architecture and Civil Engineering, Xiamen University, Xiamen, Fujian, 361005, China

Abstract

This paper establishes a bank credit decision-making system for small and medium-sized enterprises. This paper quantifies the risk of enterprises with existing credit records and reputation ratings and establishes a risk rating model. The specific financial situation of 123 enterprises with credit records and credit rating is quantified and a model is established. In this paper, a large number of original data are processed and integrated by EXCEL and MATLAB software to get six indexes, and then three representative principal component factors are extracted by principal component analysis, which are used as independent variables for binary Logistic regression analysis, the evaluation of whether the enterprise is in breach of contract is obtained, the default screening model is established, the grade of the enterprise in breach of contract is rated as IV, and then the enterprise without default is analyzed by multivariate ordered Logistic regression analysis. Establish a risk level refinement model to further refine the non-default corporate rating, that is, I-level, II-level and III-level.

Keywords

Bank credit system, Risk level, Principal component analysis, Logistic regression

Cite This Paper

Jiexin Lu, Yongzhen Tong. Research on credit risk of commercial banks based on multiple logistic model. Academic Journal of Business & Management (2021) Vol. 3, Issue 6: 83-87. https://doi.org/10.25236/AJBM.2021.030612.

References

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[2] Wang Yue, A Comparative Study of Double Model Forecasting Method for Credit Risk Identification of Listed Private Enterprises, Master Thesis of Inner Mongolia University of Science and Technology, 2020.

[3] Ma Guangjun, Research on Credit Risk Evaluation of Urban Investment Bond in China Based on Multivariate Orded Logistic Model, Master Thesis of Tianjin University of Finance and Economics, 2012

[4] Guo Qian, A Study on Specific Risk Adjustment Coefficients in the Valuation of Unlisted Companies, Master Dissertation of Beijing Jiaotong University, 2015

[5] Bian Yun, A study on hierarchical diagnosis model of chronic pancreatitis based on factor analysis with multiple ordered Logistic regression, PhD Dissertation of Second Military Medical University, 2016

[6] Zheng Fangyun, A Study on Forecasting Financial Distress of Listed Companies in China -- Based on Ordered-Triclass Logistic Regression, Master Dissertation of Zhejiang University, 2013.