Harnessing artificial intelligence and machine learning for fraud detection and prevention in Nigeria - Oluwaseun Isaac Odufisan; Osekhonmen Victory Abhulimen; Erastus Olarenwaju Ogunti (Journal of Economic Criminology)
Fraud poses a significant threat to Nigeria's burgeoning digital economy, impacting sectors like finance, e-commerce, healthcare, and education. Traditional methods struggle to keep pace with evolving fraud schemes. This paper investigates the potential of Artificial Intelligence (AI) and Machine Learning (ML) for enhanced fraud detection and prevention in Nigeria. We explore various AI methodologies, including supervised, unsupervised, and deep learning. We discuss their applications in anomaly detection, behavioural analysis, risk scoring, and network analysis. By leveraging AI's continuous learning capabilities, organizations can adapt to novel fraud tactics. The paper highlights the benefits of AI-powered fraud detection, including increased efficiency, improved accuracy, and proactive risk mitigation. However, challenges like technical limitations and regulatory considerations are acknowledged. Lastly, we examine the promising future of AI and ML in transforming the financial crime prevention situation in Nigeria.