Mining of Credit Risk Factors for New Agricultural Entities under the Big Data of Agricultural Economy in Jilin Province

DOI

10.2991/978-94-6463-490-7_35How to use a DOI?

Keywords

Credit Risk Factors; Agricultural Economic Big Data; Support Vector Machine; New Agricultural Entities; Jilin Province

Abstract

The excavation of credit risk factors for new agricultural entities plays an important role in providing comprehensive credit evaluation and promoting stable growth of the agricultural economy. The current traditional mining methods lack objectivity and accuracy, making it difficult to provide effective support for the credit evaluation of new agricultural entities. In order to improve the effectiveness of credit risk factor mining and promote the healthy development of agricultural economy, this article takes Jilin Province as the research object and combines agricultural economic big data to conduct in-depth research on the mining of credit risk factors for new agricultural entities. This article first analyzes the current situation of agricultural economy and the development of new agricultural entities in Jilin Province. Then, computer technology is used to process big data of Jilin Province's agricultural economy. Finally, based on the big data of agricultural economy, credit risk factors of new agricultural entities are excavated. And experimental analysis was conducted on credit risk factors. The results show that moral credit, business scale, market demand, and environmental risks have a key impact on the credit risk of new agricultural entities. In the analysis of impact degree, compared with the default rate in January, under the influence of these four factors, the default rate in December increased by 6.65%, 6.45%, 4.84%, and 5.54%, respectively. The conclusion indicates that agricultural economic big data can objectively explore the credit risk factors of new agricultural entities and achieve more accurate information risk assessment.

Copyright

© 2024 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  - Chunhui Wang
PY  - 2024
DA  - 2024/08/31
TI  - Mining of Credit Risk Factors for New Agricultural Entities under the Big Data of Agricultural Economy in Jilin Province
BT  - Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
PB  - Atlantis Press
SP  - 322
EP  - 332
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-490-7_35
DO  - 10.2991/978-94-6463-490-7_35
ID  - Wang2024
ER  -