Artificial Intelligence in Risk Management and Financial Stability in Nigeria

This study investigates the impact of Artificial Intelligence (AI) applications risk management specifically AI-based credit scoring, AI-driven fraud detection, and AI-powered predictive analytics on financial stability (asset quality) in Nigerian banks. A survey research design was adopted, with primary data collected from 141 respondents across 15 selected banks, mainly from risk management, IT, and finance departments, representing a 94% response rate. The study employs descriptive statistics to summarize respondent demographics and AI adoption patterns, while multiple regression analysis examines the effect of AI on financial stability and asset quality. The analysis shows that AI adoption significantly enhances financial stability and asset quality. AI in risk management exhibits a positive and significant effect (B = 0.556, β = 0.836, t = 9.711, p < 0.001). AI-based credit scoring positively impacts asset quality (B = 0.440, β = 0.614, t = 8.483, p < 0.001), improving loan approval accuracy, reducing non-performing loans, and enhancing fairness in credit allocation. AI-driven fraud detection demonstrates a strong positive effect (B = 0.592, β = 0.842, t = 18.370, p < 0.001), reducing fraudulent transactions, lowering financial losses, and increasing operational security. Predictive analytics significantly improves asset quality (B = 0.210, β = 0.492, t = 6.658, p < 0.001), supporting proactive risk management, liquidity monitoring, and regulatory compliance. The study also finds that AI adoption is more pronounced in commercial banks (61%) than merchant banks (39%) and among experienced staff with 11–15 years’ experience (41.8%). In conclusion, AI technologies are strategic tools that strengthen risk management, asset quality, and overall financial system stability in Nigeria. The study recommends further investment in AI, continuous staff training, and regulatory support to maximize adoption and financial resilience.