REVIEW OF LITERATURE ON AI AND ITS APPLICATIONS IN THE BANKING SECTOR

Artificial Intelligence (AI) has significantly transformed the banking sector by enhancing decision-making, automating processes, and improving customer experience. This paper reviews the evolution of AI in banking, tracing its development from expert systems in the 1980s to advanced machine learning and deep learning models in the present day. The study examines key AI applications, including credit risk assessment, fraud detection, customer service, and regulatory compliance. Comparative performance analysis of AI models such as logistic regression, decision trees, neural networks, and support vector machines highlights their effectiveness in various banking functions. While AI adoption has improved operational efficiency and customer engagement, challenges related to data privacy, algorithmic bias, and regulatory compliance remain significant. The paper also discusses future prospects, emphasizing the potential of AI in expanding financial inclusion and the need for improved AI explainability and fairness. Recommendations for enhancing AI implementation and addressing associated challenges are provided.

Keywords: Artificial Intelligence, Banking Sector, Machine Learning, Credit Risk, Fraud Detection, Customer Service, Financial Inclusion

 Artificial Intelligence Banking Sector Machine Learning Credit Risk Fraud Detection Customer Service Financial Inclusion