DefinePK

Abstract

The increasing complexity and digitalization of supply chain systems in the United States have heightened the risk of fraudulent activities, resulting in significant financial losses and reputational damage to businesses. Artificial Intelligence (AI)-driven approaches offer a transformative solution for real-time fraud detection by leveraging advanced analytics, machine learning algorithms, and predictive modelling to identify anomalies and suspicious patterns across logistics, procurement, and financial transactions. This paper explores the integration of AI technologies into supply chain management (SCM) for proactive fraud detection, examining both the challenges and opportunities inherent in these systems. Key AI techniques such as neural networks, natural language processing, and unsupervised learning are discussed in the context of detecting procurement fraud, counterfeit product insertion, cyber intrusions, and supplier collusion. While the implementation of AI enhances speed and accuracy in fraud identification, it also introduces challenges including data privacy concerns, model bias, lack of transparency, high implementation costs, and the need for robust data governance frameworks. Moreover, limited AI literacy among supply chain personnel and resistance to technological change impede widespread adoption. Opportunities lie in the use of AI for real-time monitoring, supply chain visibility, and integration with blockchain for immutable audit trails, which collectively strengthen fraud resilience. The study also highlights the importance of cross-sector collaboration, regulatory alignment, and the development of interoperable systems to enhance data sharing and risk management. By evaluating successful case studies from leading U.S. supply chain firms and government agencies, the paper offers a roadmap for leveraging AI in a scalable, ethical, and cost-effective manner. Ultimately, the paper underscores that AI-powered fraud detection in supply chains is not merely a technological upgrade but a strategic imperative for securing assets, safeguarding stakeholder trust, and enhancing national economic stability. As the U.S. advances toward intelligent supply networks, AI presents both an urgent challenge and a significant opportunity for shaping the future of supply chain risk management.
Keywords: Artificial Intelligence, Fraud Detection, Supply Chain Management, Real-Time Analytics, Machine Learning, Predictive Modeling, Blockchain, Anomaly Detection, Procurement Fraud, U.S. Supply Chain.