AI IN FINANCIAL RISK ASSESSMENT: A REVIEW STUDY

Abstract

This review study explores the application of Artificial Intelligence (AI) techniques in financial risk assessment, highlighting recent advancements, methodologies, and challenges. AI-driven models, including machine learning, deep learning, and natural language processing, have significantly enhanced the accuracy and efficiency of identifying, measuring, and managing various types of financial risks such as credit risk, market risk, and operational risk. The study synthesizes current research findings, evaluates the effectiveness of different AI algorithms, and discusses the integration of AI with traditional risk management frameworks. Furthermore, it addresses ethical considerations, data quality issues, and regulatory implications. The review concludes by identifying future research directions to optimize AI applications in the evolving landscape of financial risk assessment.