The Research of Agricultural SMEs Credit Risk Assessment Based on the Supply Chain Finance

Agriculture is a basic industry that supports the construction and development of the national economy and plays an important role in promoting rural revitalization. And in the current post-COVID-19 era, agricultural SMEs have difficulty in obtaining the favours of financial institutions in normal l...

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Bibliographic Details
Published in:E3S web of conferences 2021-01, Vol.275, p.1061
Main Authors: Tong, Zeping, Yang, Shuo
Format: Article
Language:English
Subjects:
Agricultural development
Agricultural economics
Agricultural research
COVID-19
Credit risk
Economics
Factor analysis
Finance
Financial management
Financing
Growth factors
Modernization
Profitability
Regeneration
Risk assessment
Risk management
Small business
Supply chains
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Summary:Agriculture is a basic industry that supports the construction and development of the national economy and plays an important role in promoting rural revitalization. And in the current post-COVID-19 era, agricultural SMEs have difficulty in obtaining the favours of financial institutions in normal lending due to their weak credit guarantee capabilities and high credit management costs. Difficulty in financing has become a bottleneck problem that plagues the development of enterprises and restricts the development of agricultural modernization. How to evaluate and control its credit risk is not only a major way to solve the financing difficulties of agricultural SMEs, but also the basis for the stable development of supply chain financial services. This paper analyzes three typical financing modes of agricultural SMEs from the perspective of supply chain finance, and takes the agricultural SMEs in the New OTC Market as an example to construct a Logistic model, and uses factor analysis to effectively predict the credit risk of supply chain finance. The results show that the operational efficiency factors, growth factors and related core corporate profitability of agricultural SMEs financing enterprises significantly affect their credit risk. After testing, the model is highly accurate in predicting the financing risks of agricultural SMEs.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202127501061