A Scalable Framework for Intelligent Automation in Retail and Commercial Banking Operations

Abstract

The proliferation of artificial intelligence (AI) and robotic process automation (RPA) technologies has revolutionized back-office processes across the banking sector. However, achieving scalable, adaptable, and governance-aligned intelligent automation remains a challenge, especially for institutions navigating complex regulatory environments. This paper proposes a framework tailored for both retail and commercial banking that integrates AI, RPA, machine learning (ML), and decision intelligence into a cohesive, scalable ecosystem. We validate our approach through comparative analysis, industry benchmarks, and use case modeling, highlighting operational efficiency, accuracy, and compliance improvements.