A Scalable Framework for Intelligent Automation in Retail and Commercial Banking Operations
Keywords:
Intelligent Automation, Robotic Process Automation (RPA), Retail Banking, Commercial Banking, Machine Learning, Decision Intelligence, Digital TransformationAbstract
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.
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Copyright (c) 2025 Wisma Yenni Darwis (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
