Applications of Artificial Intelligence for Optimizing Banking and Financial Operations: A Systematic Literature Review and Future Research Agenda

Artificial intelligence (AI) is rapidly changing the banking and financial system, taking over fundamental operations to improve operational efficiencies and minimize costs. Although scholarly research has focused either on the implications of machine learning (ML) and deep learning algorithms to improve the performance of the banking and financial sectors or on the applications of AI in specific banking or financial operations, insights into the overall growth of AI in the banking and financial sectors but its applications in diverse functional areas of the banking and financial sectors are relatively scarce. This study aims to present a systematic literature review on the current state of knowledge of AI in banking and the financial sector. A systematic review of 157 articles was conducted to identify, select, assess, and synthesize relevant studies on this phenomenon and was analyzed for emerging themes. The thematic analysis revealed several key themes, including AI as an innovation in customer service, AI applications and customer readiness, AI adoption and financial inclusion, AI adoption and regulation, and AI applications and their explainability. It also identified various applications of, and barriers to, AI adoption. Furthermore, the study proposes a research framework and develops propositions that can be tested in future research. Finally, the study provides a future research agenda based on a theory, context, and methodology (TCM) framework and discusses the study's implications.