The Role Of Big Data Analytics And Artificial Intelligence In Modern Banking: A Multi-Applications Analysis

Abstract

To be competitive in a time of fast digital transformation, banks have to welcome developing technologies—especially artificial intelligence (AI) and big data analytics (BDA). National and international banks all over are working to develop their offerings to keep clients, draw new business, and boost profits. Still, artificial intelligence applications in banking largely consist in chatbots or back-office process automation. With an eye toward commercial banks especially, this article investigates the larger prospects and useful applications of artificial intelligence and BDA in the banking industry. It seeks to give a thorough summary of current scholarly work and point up untapped prospects for next study. Although there are many use applications, the paper focuses on important topics including fraud detection, loan default prediction, credit scoring, and tailored marketing. Apart from evaluating developments in data preprocessing methods and machine learning approaches, this work especially addresses the influence of dataset size on model performance. This helps to design stronger, scalable, and efficient AI-powered financial systems by exposing the methodological shortcomings of some studies.