Advanced risk management models for supply chain finance
1 Livingstone Integrated Technology Limited, Lagos, Nigeria.
2 Independent Researcher, London, United Kingdom.
3 Ulster University, United Kingdom.
4 Independent Researcher, Abuja, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 22(02), 612–618
Publication history:
Received on 02 April 2024; revised on 07 May 2024; accepted on 10 May 2024
Abstract:
This review paper delves into the transformative potential of advanced risk management models in enhancing the resilience and efficiency of supply chain finance (SCF). By examining the application and development of Artificial Intelligence (AI), Machine Learning (ML), Big Data analytics, and blockchain technology, the paper highlights their role in transitioning from traditional reactive strategies to proactive and predictive risk management approaches. Despite the promising advantages, the paper also addresses the significant implementation challenges, model limitations, and regulatory and ethical considerations accompanying these technological advancements. Recommendations for effective deployment and areas for future research, particularly in overcoming existing hurdles and exploring emerging technologies, are also discussed. This comprehensive analysis aims to guide academics, industry professionals, and policymakers in harnessing advanced risk management models for a more robust SCF ecosystem.
Keywords:
Supply Chain Finance; Risk Management; Artificial Intelligence; Blockchain Technology; Big Data Analytics; Predictive Models
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0