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A New Model System of Optimal Revenue and Rating Classification Based on Credit Strategy

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DOI: 10.23977/infse.2021.020105 | Downloads: 0 | Views: 109

Author(s)

Jie Xiang 1, Yi Wu 1, Qian Gong 1

Affiliation(s)

1 School of Science, Hangzhou Normal University, Hangzhou, Zhejiang, 311121

Corresponding Author

Jie Xiang

ABSTRACT

According to the credit, scale, strength and other indicators of different enterprises, banks comprehensively judge whether they want to lend to enterprises, the amount of loan, interest rate and term. Small, medium and micro enterprises occupy a large scale in the market. How to analyze the credit risk of small, medium and micro enterprises and get the optimal credit strategy? In this paper, a new model system is established, which is called “optimal revenue and rating classification”. The “optimal revenue” is the optimal revenue risk model, and the “credit rating” is the credit rating classification model. This paper analyzes eight indicators of credit risk, uses Python to quantify the data, imports them into Matlab for grey correlation analysis, and normalizes the results. Analyze and explain the standardized data, get the reciprocal weight of each enterprise credit risk, establish the optimal income risk model according to the principle of high income and low risk, solve the model with Matlab, and get the optimal annual interest rate for each enterprise. According to the different credit rating of enterprises, combined with the risk index to determine the credit line formula.

KEYWORDS

optimal revenue and rating classification, optimal revenue risk, credit rating classification

CITE THIS PAPER

Jie Xiang, Yi Wu, Qian Gong. A New Model System of Optimal Revenue and Rating Classification Based on Credit Strategy. Information Systems and Economics (2021) 2: 27-30. DOI: http://dx.doi.org/10.23977/infse.2021.020105

REFERENCES

[1] Zhang Di. Research on green credit risk assessment of commercial banks in China -- Based on fuzzy analytic hierarchy process and BP neural network algorithm [J]. Shanxi Agricultural Economics, 2019 (05): 147-148;
[2] VAT reform [J]. Tianjin economy, 2011 (11): 82;

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