Predicting Supply Chain Fraud with Artificial Intelligence and Machine Learning Models: Enhancing Operational Security and Integrity

Companies are under increasing pressure to discover novel approaches to optimizing efficiency and reducing costs as a result of the growing complexity of supply networks. The use of machine learning (ML) and artificial intelligence (AI) in supply chain management is one area that has witnessed significant growth in recent years. This proposed uses AI and machine learning techniques to foretell instances of supply chain fraud. Actual company transactions provided the supply chain data used in this project. It turns out that AI and ML classifiers were very good at predicting fraud in the supply chain. Specifically, after looking at all performance metrics, the AI model emerged as the top predictor. According to these findings, AI has the potential to be an effective weapon in the fight against supply chain fraud. When it comes to analysing large datasets, ML and AI classifiers can find patterns that humans might miss. This paper's findings can be applied to optimize supply chain management (SCM) and to anticipate fraudulent transactions. Machine learning and artificial intelligence classifiers may change supply chain management for the better, but they are still in their infancy.