The Impact of Artificial Intelligence on Financial Risk Management: Opportunities and Challenges in the Post-2025 Era

Abstract

This article examines the transformative role of artificial intelligence (AI) in financial risk management following the market disruptions of 2025. Drawing on empirical data from major global banks and fintech firms, it explores how AI-driven models enhance predictive accuracy, automate compliance, and mitigate systemic risks. The study employs a mixed-methods approach, including quantitative analysis of credit risk datasets and qualitative interviews with industry executives. Key findings reveal a 35% improvement in risk forecasting precision using machine learning algorithms, though ethical concerns and regulatory gaps persist. Practical implications include recommendations for hybrid AI-human frameworks to balance efficiency and accountability. This research contributes to the literature by bridging theoretical risk models with real-world AI implementations in a volatile economic landscape.