Paper Title
Exploring the Role of Artificial Intelligence in Supply Chain Finance: A Systematic Review

Abstract
This paper provides a systematic review of the academic literature on the use of Artificial Intelligence (AI) in the field of Supply Chain Finance (SCF). As supply chains become increasingly complex and data-driven, AI technologies have emerged as powerful tools to enhance financial flows, optimize working capital, and improve decision-making across supply chain partners. Based on a rigorous selection of peer-reviewed articles published between 2010 and 2025, this study synthesizes key findings and classifies AI applications in SCF into four main categories: credit risk assessment and financing decisions, invoice and payment automation, fraud detection, and dynamic discounting and trade finance optimization. The review highlights how machine learning, natural language processing, and other AI techniques contribute to increased transparency, cost efficiency, and resilience in SCF practices. However, the analysis also reveals critical research gaps, including data governance, ethical concerns, regulatory constraints, and the need for industry-specific AI models. The paper concludes by proposing a future research agenda and offering managerial implications for leveraging AI to create more agile and financially sustainable supply chains. Keywords - Artificial Intelligence, Supply Chain Finance, Machine Learning, Risk Assessment, Invoice Automation, Trade Finance, Systematic Literature Review.