Agentic AI in retail banking

Executive Summary

Over the last two and a half decades, artificial intelligence (AI) and technological innovation have evolved exponentially within the banking sector. Since the early 2000s, AI in banking has evolved from basic fraud detection and customer support to include credit scoring, risk assessment and algorithmic trading. Today, it has become integral to personalized banking, chatbots, fraud prevention, and compliance monitoring. This article explores the shift from reactive to autonomous, goal-driven AI, focusing on how agentic AI is redefining retail banking by enhancing customer experiences and streamlining operations through proactive decision-making. This integration marks a shift from experimental to enterprise-wide implementation, with AI in retail banking establishing itself as an intrinsic component of the digital experience. Moving away from pilot programs, some form of AI is now integrated across most banking operations. AI-powered assistants, machine-learning models and fraud detection are now all at the heart of most modern banking infrastructures. With rising consumer demands for faster digital service, the need for more autonomous, goal-driven AI models is more crucial than ever to enhance the customer experience and ensure optimal efficiency.