The Quantitative Analysis and Decision-making of MSMEs’ Credit Risk

Abstract

In this study, we focused on the quantitative analysis and decision-making of credit risk of the Micro, Small and Medium Enterprises (MSMEs) from the perspective of bank. Based on the data of 123 MSMEs, we extracted and processed information from the original data with theoretical analysis and feature engineering, and established an entropy weight-TOPSIS model to get the credit risk index of each MSME. Meanwhile, the credit strategy optimization model was constructed, and the DE algorithm was used to solve the credit strategy scheme for bank to each MSME. According to the relationship between the total annual credit of bank, interest rate and expected profit, we analyzed the partial sensitivity of the model and explored the maximum profitability of the bank and finally gave helpful suggestions. Our results have guiding significance for banks to manage and make decisions on the credit risk of MSMEs.

Utilization of Big Data for SWOT Analysis in Improving Business Sustainability of MSMEs

“…Risk can be defined as a state of uncertainty, in which the occurrence of an unpleasant can result in a loss. Business operations inherently entail various risks (Tao et al, 2021). Risk management has a significant impact on corporate activity.…”