Issue |
SHS Web Conf.
Volume 169, 2023
4th International Symposium on Frontiers of Economics and Management Science (FEMS 2023)
|
|
---|---|---|
Article Number | 01004 | |
Number of page(s) | 4 | |
DOI | https://doi.org/10.1051/shsconf/202316901004 | |
Published online | 29 May 2023 |
Optimal credit strategy for MSMEs
North China Electric Power University, Baoding, Hebei Province, China
* Corresponding author: 2628763305@qq.com
We address two main issues: one is to quantify the credit risk of enterprises and establish a complete credit risk system, and the other is to give the optimal credit risk strategy for banks. We first analyze and pre-process the data. From the data, we extracted a series of indicators such as the total amount of input and output, and the length of operation. We analyze the credit risk in three directions: strength, stability of supply and demand, and creditworthiness, and establish a credit risk quantification system for the enterprise. Then we quantify the credit risk of the enterprise by entropy method and TOPSIS. Second, a function is fitted to the bank’s customer churn rate and the bank’s lending rate. Using a planning-type model, the credit decisions of the firms are required to be given. We follow the principle of maximizing benefits and minimizing risks to build a multi-objective planning model. We base on the scores of each firm that have been solved, for the classification of firms, and follow the principle of low credit risk, low lending rate, and set the corresponding lending rate for each type of firm. The model is solved by the through-order solution method, and the linear weighting method is used to test the comparison. The credit decision for each enterprise is given.
Key words: Entropy method / TOPSIS / Multi-objective planning model
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.