A Comprehensive Review on Applications of Artificial Intelligence in Stock Analysis, Credit Risk and Portfolio Management: Advancements, Challenges and Future Directions

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in financial modelling, revolutionizing the way financial institutions analyse data, make decisions, and manage risks. This comprehensive review manuscript examines the state-of-the-art applications, advancements, challenges and future directions of AI in financial modelling across stock analysis, credit risk and portfolio management. The review starts with an overview of AI technologies relevant to financial modelling, including machine learning and deep learning. AI has its applications in financial modelling, such as stock market prediction, credit risk assessment, algorithmic trading, fraud detection, portfolio optimization, and regulatory compliance. The manuscript discusses the importance of AI in enhancing decision-making processes, improving efficiency, and mitigating risks in the dynamic and complex landscape of finance. Furthermore, it addresses the challenges and limitations associated with the use of AI in financial modelling, such as data quality issues, interpretability concerns, regulatory constraints, and ethical considerations. Finally, the manuscript outlines future directions and emerging trends in AI-enabled financial modelling, highlighting opportunities for innovation, collaboration, and responsible AI governance. Finally, this review provides valuable insights and recommendations for practitioners, researchers, and policymakers interested in harnessing the potential of AI to drive advancements in financial modelling and shape the future of finance.