Artificial Intelligence for Financial Risk Management and Analysis

Financial institutions face dynamic threats that range from credit defaults to money laundering. Traditional risk management models struggle with large data and shifting market conditions. Artificial intelligence (AI) offers flexible, data-driven methods that enhance credit scoring, fraud detection, market analytics, and compliance. By leveraging supervised, unsupervised, and reinforcement learning, AI-based solutions identify patterns, adapt to emerging threats, and automate complex processes. However, these approaches require robust governance to maintain fairness, interpretability, and security. This paper surveys AI's applications in financial risk, discusses challenges in deployment, and highlights future directions, including explainable AI, federated learning, and integrated RegTech solutions, requiring oversight.