AI is a revolutionary force that could disrupt several sectors. This chapter addresses key questions about AI's impact on banking. It examines natural language processing, machine learning, and predictive analytics in finance. The study aims to elucidate how AI can enhance the banking experience for customers by exploring its role in personalized services, customer support, and fraud prevention. Further, it offers a comprehensive analysis of the pros and cons of utilizing AI in banking operations, illuminating the potential ethical and societal difficulties that may arise as a result. The research examines how AI can improve banking efficiency, transforming the business. The study's main objective is to inform industry stakeholders, policymakers, and researchers on the pros and downsides of AI adoption in this vital sector by addressing the significant AI in banking issues. This study sets the stage for a comprehensive exploration of AI's transformative potential in the banking landscape.
Top2. Methodology
A comprehensive review of scholarly and industry publications is conducted to gather information on artificial intelligence's application to banking (Brynjolfsson & Mitchell, 2017; Mikhalkina & Cabantous, 2015). The literature review is structured around primary applications of AI in banking, such as fraud detection, customer service, and personalized financial advice (Gupta & Jayaraman, 2021; Guo et al., 2021; Lipton et al., 2018). The review examines the different types of AI technologies currently being utilized in banking, including natural language processing, machine learning, and predictive analytics (Li & Zhang, 2021; Panigrahi et al., 2021). And, this research seeks to answer several important questions about artificial intelligence (AI) in the banking business, including what role AI plays, what benefits and obstacles are connected with its use, and how AI may be applied to improve customer experience and operational efficiency (Geetha and Uma, 2021). The idea sheds light on sensitive topics like data privacy (Kshetri and Voas, 2021; Yang, Liu, and Guo, 2020), increased efficiency, reduced costs, and enhanced security (Li & Zhang, 2021; Mikhalkina & Cabantous, 2015) and bias that arise when using AI to the banking industry.
By performing a thorough investigation of the impact and integration of AI technologies in the banking sector, this paper attempts to respond to the following research topics: