Early Warning Method of Credit Risk of Agricultural Enterprises in Guizhou Province Based on AHP

DOI

10.2991/978-94-6463-198-2_66How to use a DOI?

Keywords

AHP; Agriculture; credit; Enterprise; Guizhou Province; Risk early warning

Abstract

As the basic industry and traditional industry of the national economy, agriculture plays an extremely important role in economic development, especially in today’s global food shortage and frequent natural disasters. The supporting position of agriculture is becoming more and more important. Agricultural enterprises, as a channel for the transformation of agricultural value, have gradually received widespread public attention. Therefore, in order to promote the stable development of society, agricultural enterprises must combine their own actual situation, objectively predict the risks they face, and take preventive measures. To realize the accurate early warning of enterprise credit risk, this paper introduces the analytic hierarchy process (AHP) multi-level analysis, and takes agricultural enterprises in Guizhou Province as an example to carry out the research on the design of credit risk early warning method. Based on the current background of supply chain finance, this paper selects the enterprise credit risk early warning indicators and establishes an index system. Through using the AHP, it analyzes the influencing factors of each indicator and the degree of influence, and establishes an enterprise credit risk evaluation model; it takes the default probability calculation value as the condition to judge whether to output early warning signals, and realizes enterprise credit risk early warning. Through the application of the new early warning method in practice, it is proved that the method can realize the early warning of credit risk. According to the early warning results, the specific direction of improving credit degree can be determined, which can promote the improvement of enterprise credit degree.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Manxue Zhang
AU  - Ni Li
AU  - Chang Zhang
PY  - 2023
DA  - 2023/08/10
TI  - Early Warning Method of Credit Risk of Agricultural Enterprises in Guizhou Province Based on AHP
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 645
EP  - 652
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_66
DO  - 10.2991/978-94-6463-198-2_66
ID  - Zhang2023
ER  -