Credit Analysis of Small and Medium Sized Enterprises based on Logistic Regression
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DOI: 10.23977/EMCG2020.015
Author(s)
Zhao Qiuya, Cheng Chi, Xu Hailin
Corresponding Author
Zhao Qiuya
ABSTRACT
Credit is one of the indispensable economic activities in modern society. Its emergence helps a large number of enterprises, especially small and medium-sized enterprises out of the predicament, and plays an important role in the economic development of enterprises. Based on credit, this paper gives the risk quantification and bank lending strategy for small and medium-sized enterprises. This paper analyzes the risk of 123 credit enterprises. In this paper, we use the trade notes and their names to formulate appropriate data and extract the information of the upstream and downstream industries and the strength of the company. Then, we use TOPSIS model to quantify the strength and reputation of the industry and the enterprise itself. At the same time, through the analysis, we found that the breach of contract is closely related to its own factors, but not to the industry. Therefore, we use the established enterprise strength and reputation index to carry out logistic regression, and get the expression of the enterprise's own index and its forecast default probability. After forecasting the default probability of an enterprise, the default probability is taken as the result of quantitative risk. Then, using single objective programming, taking the interest rate of enterprise loan as the decision variable, the maximization of bank loan income is taken as the goal.
KEYWORDS
Quantitative analysis, Logistic regression, TOPSIS model