The Role of Artificial Intelligence in Shaping the Future of Banking Operations

Abstract

The study synthesises research on the adoption, applications, benefits, risks, and governance of artificial intelligence (AI) in banking operations. The proposed research applied a PRISMA-based search and screening process to peer-reviewed journals, industry reports, and high-quality preprints (2015–2025) to answer: what AI techniques and applications are used in banking operations?, What operational benefits have been reported? What risks, limitations and regulatory challenges arise? What are the gaps and directions for future research? Major application areas include fraud detection and anti-money laundering (AML), credit scoring and underwriting, customer-facing automation (chatbots or virtual assistants), robotic process automation (RPA) for back-office processing, risk modelling and portfolio optimisation, and robo-advisory or investment automation. The reported benefits are improved detection accuracy and speed, operational cost reductions, enhanced customer experience, and better real-time risk monitoring. Key concerns include model explainability, data quality and bias, legal or compliance constraints, systemic risk amplification, and governance or auditability. The study concludes with a proposed research agenda that emphasises explainable AI (XAI), model risk management, data governance, human-AI collaboration, and regulatory sandboxes to scale AI in banking safely.