Artificial Intelligence-Driven Internal Control Systems and Cybercrime Prevention in Nigerian Deposit Money Banks

Abstract

The rapid advancement of digital banking services has significantly transformed the operations of financial institutions by improving efficiency, accessibility, and service delivery. However, this increased dependence on digital platforms has also created new vulnerabilities, exposing Deposit Money Banks (DMBs) to emerging cybercrime threats such as electronic fraud, unauthorized access, data breaches, and other forms of cyber-attacks. The limitations of traditional internal control mechanisms, which often rely on manual procedures and periodic monitoring, have created the need for more intelligent and proactive control approaches. This study examined the effect of artificial intelligence-driven internal control systems on cybercrime prevention in Nigerian Deposit Money Banks. The study was anchored on Agency Theory and adopted a survey research design. Data were obtained through structured questionnaires administered to employees involved in information technology security, internal audit, and risk management functions within selected Nigerian Deposit Money Banks. A sample size of 250 respondents was drawn from a population of 1,255 employees using a stratified random sampling technique. The collected data were analysed using descriptive statistics and multiple regression analysis with the aid of SPSS version 28. The findings revealed a strong positive relationship between artificial intelligence-driven internal control systems and cybercrime prevention (R = 0.741). The results further showed that AI-driven internal control systems accounted for 54.9% of the variation in cybercrime prevention (R² = 0.549). The regression analysis also indicated that artificial intelligence-driven internal control systems have a positive and statistically significant effect on cybercrime prevention (β = 0.612, p = 0.000). The study concluded that artificial intelligence-driven internal control systems improve cybercrime prevention by strengthening real-time monitoring, anomaly detection, fraud identification, and proactive risk management practices within Nigerian Deposit Money Banks. The study recommends that banks should continue to invest in AI-based control technologies, develop employees’ capacity in artificial intelligence applications, and establish appropriate governance structures to ensure effective and responsible deployment of AI solutions.