Risk Assessment and Management in the Age of Artificial Intelligence for Banking, Finance, and Insurance

Abstract

Risk assessment and management are central pillars of the banking, finance, and insurance sectors. The adoption of artificial intelligence (AI) and machine learning (ML) is revolutionizing these processes, enabling faster and more accurate risk evaluation. AI-powered models can detect patterns, predict defaults, and optimize underwriting processes with higher precision than traditional methods. However, reliance on AI also introduces challenges such as algorithmic bias, lack of transparency, and regulatory concerns. This paper investigates AI-driven risk management frameworks, their applications in BFI, and the emerging challenges. It highlights how AI can enhance predictive capabilities while emphasizing the need for robust governance structures to ensure ethical and transparent implementation.

KEYWORDS: Artificial Intelligence, Risk Management, Credit Assessment, Predictive Analytics, Ethical AI