Augment Legal Efforts through Artificial Intelligence in Curtailing Economic Fraud in Nigeria: Issues and Challenges - Erma Rusdiana; Paul Atagamen Aidonojie; Muwaffiq Jufri; Hassan Ismaila; Nathan Ibrahim (IJCLS (Indonesian Journal of Criminal Law Studies), 2025)
The rise of economic fraud in Nigeria is one of the greatest threats to the financial stability of the nation, the governance systems, and socio-economic development. Though there are legal frameworks in curtailing economic fraud, there seem to be several challenges given the sophisticated economic frauds that have evolved. Therefore, this study aimed to examine AI as a transformative tool to supplement Nigeria's legal framework in its legal fight against economic fraud through facilitating the improvement of violation detection, automation of evidence gathering, and support of data-driven policymaking. It also enhances efficiency in law enforcement via predictive analytics and real-time monitoring systems. The study adopts a qualitative methodology, including an analysis of the legal framework and a literature review on AI in combating economic fraud. The findings show that despite some legal frameworks put in place for economic fraud, the legal mechanisms for the detection, prevention, and prosecution of economic fraud lack adequate capacity and nearly totally lack a procedural perspective. Also, in the study, it was found that AI technologies such as machine learning and natural language processing can help in providing means for those datasets to find some patterns, improving forensic investigations and decision-making processes in fraud cases. Thus, it stipulates that integrating AI into Nigeria's Legal Framework is essential for combating economic fraud. Policy reforms, capacity-building programs, and investment in AI infrastructure have been recommended to facilitate its adoption.