Forensic Investigation and Fraud Detection in Nigeria: Leveraging on Artificial Intelligence

Abstract

Corporate fraud continues to threaten the sustainability of businesses in Nigeria, with conventional detection methods proving inadequate in addressing the complexity and scale of fraudulent activities. This study explores the role of Artificial Intelligence (AI) in enhancing forensic investigations for fraud detection within Nigerian firms. Using a documentary approach, the study examines various AI-driven technologies, including data analytics, machine learning algorithms, and predictive modeling, in improving the speed, accuracy, and efficiency of fraud detection. Findings reveal that while integrating AI in forensic investigations poses challenges, AI-powered techniques significantly enhance fraud detection by identifying anomalies, analyzing large datasets, and enabling proactive fraud prevention through continuous monitoring. The study recommends that Nigerian firms prioritize AI integration by adopting data-driven forensic frameworks and investing in predictive modeling and machine learning algorithms. Additionally, regular training for forensic teams on AI tools is essential to maximize their effectiveness. Collaboration with AI service providers and forensic experts is also crucial to developing customized AI solutions that address the specific fraud detection needs of Nigerian businesses. By embracing AI-driven forensic investigations, Nigerian firms can strengthen their fraud detection mechanisms, reduce financial losses, and enhance overall corporate governance and sustainability.