Supply Chain Fraud Prediction with Machine Learning and Artificial intelligence

Abstract

The increasing complexity of supply chains is putting pressure on businesses to find new ways to optimize efficiency and cut costs. One area that has seen a lot of recent development is machine learning (ML) and artificial intelligence (AI) to help manage supply chains. This paper employs machine learning (ML) and artificial intelligence (AI) algorithms to predict fraud in the supply chain. Supply chain data for this project was retrieved from real-world business transactions. The findings show that ML and AI classifiers did an excellent job predicting supply chain fraud. In particular, the AI model was the highest predictor across all performance measures. These results suggest that computational intelligence can be a powerful tool for detecting and preventing supply chain fraud. ML and AI classifiers can analyze vast amounts of data and identify patterns that may evade manual detection. The findings presented in this paper can be used to optimize supply chain management (SCM) and make predictions of fraudulent transactions before they occur. While ML and AI classifiers are still in the early stages of development, they have the potential to revolutionize SCM. Future research should explore how these techniques can be refined and applied to other domains.

AI in supply chain optimization: A comparative review of USA and African Trends

“…The application of AI in supply chain management extends beyond performance enhancement, with studies emphasizing its role in quality enhancement, fraud prediction, and resilience analytics within supply chains (Tang & Lau, 2009;Lokanan & Maddhesia, 2022;Goodarzian et al, 2021). Moreover, AI has been recognized as an enabler for sustainable supply chains, offering solutions for risk mitigation and sustainable financing streams (Naz et al, 2021;Pawlicka & Bal, 2022).…”