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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2411.07604 |
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| _version_ | 1866916478222073856 |
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| author | Wan, Qiang Cui, Jun |
| author_facet | Wan, Qiang Cui, Jun |
| contents | This paper explores the impact of banking fintech on reducing financial risks in the agricultural supply chain, focusing on the secondary allocation of commercial credit. The study constructs a three-player evolutionary game model involving banks, core enterprises, and SMEs to analyze how fintech innovations, such as big data credit assessment, blockchain, and AI-driven risk evaluation, influence financial risks and access to credit. The findings reveal that banking fintech reduces financing costs and mitigates financial risks by improving transaction reliability, enhancing risk identification, and minimizing information asymmetry. By optimizing cooperation between banks, core enterprises, and SMEs, fintech solutions enhance the stability of the agricultural supply chain, contributing to rural revitalization goals and sustainable agricultural development. The study provides new theoretical insights and practical recommendations for improving agricultural finance systems and reducing financial risks.
Keywords: banking fintech, agricultural supply chain, financial risk, commercial credit, SMEs, evolutionary game model, big data, blockchain, AI-driven risk evaluation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_07604 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dynamic Evolutionary Game Analysis of How Fintech in Banking Mitigates Risks in Agricultural Supply Chain Finance Wan, Qiang Cui, Jun Econometrics This paper explores the impact of banking fintech on reducing financial risks in the agricultural supply chain, focusing on the secondary allocation of commercial credit. The study constructs a three-player evolutionary game model involving banks, core enterprises, and SMEs to analyze how fintech innovations, such as big data credit assessment, blockchain, and AI-driven risk evaluation, influence financial risks and access to credit. The findings reveal that banking fintech reduces financing costs and mitigates financial risks by improving transaction reliability, enhancing risk identification, and minimizing information asymmetry. By optimizing cooperation between banks, core enterprises, and SMEs, fintech solutions enhance the stability of the agricultural supply chain, contributing to rural revitalization goals and sustainable agricultural development. The study provides new theoretical insights and practical recommendations for improving agricultural finance systems and reducing financial risks. Keywords: banking fintech, agricultural supply chain, financial risk, commercial credit, SMEs, evolutionary game model, big data, blockchain, AI-driven risk evaluation. |
| title | Dynamic Evolutionary Game Analysis of How Fintech in Banking Mitigates Risks in Agricultural Supply Chain Finance |
| topic | Econometrics |
| url | https://arxiv.org/abs/2411.07604 |