Effect Of Artificial Intelligence (AI) On Fraud Detection In Deposits Money Banks In South East, Nigeria

Abstract

This study examines the impact of artificial intelligence (AI), specifically computer vision and robotic process automation (RPA), on fraud detection in Deposit Money Banks in Southeast Nigeria. AI technologies offer innovative solutions to combat rising fraud threats by enabling real-time monitoring, anomaly detection, and process automation. The study’s objectives include assessing the effectiveness of computer vision in detecting insider fraud and evaluating the role of RPA in monitoring card fraud activities. Using a descriptive survey design, data was collected from employees within various banking institutions in Southeast Nigeria via questionnaire to assess the effectiveness, challenges, and potential improvements AI technologies bring to fraud detection practices. A total population of 1101 staff were selected from the studied organizations. Sample size of two hundred and eighty four (284) was determined using Freund and William's statistic formula at 5 percent margin of error. Data was presented and analyzed using Likert Scale and the hypotheses using Z - test. The findings indicate that Computer Vision had significant positive effect on insider fraud detection, Z = 6.561< 8.639, P. <, 05. Robotics had significant positive effect on card fraud monitoring in money deposit bank in Southeast, Nigeria, Z = 7.649 < 9.987, P. <,05. The study underscores the importance of a comprehensive AIintegrated fraud detection system and recommends further exploration into cost-effective implementations tailored to the context of smaller banking institutions. Addressing these challenges can foster an improved security landscape in Nigeria’s banking sector, enhancing trust and operational resilience