Agentic AI in Finance: Building Autonomous Financial Assistants on AWS for Personalized Customer Solutions

Financial services are rapidly advancing towards highly autonomous, intelligent, and personalized solutions by integrating agentic AI (Artificial Intelligence) systems. This paper presents a comprehensive architecture and implementation of autonomous agentic AI frameworks, specifically designed for financial services, and built upon a series of Amazon Web Services (AWS) cloud technologies. We propose a scalable and secure architecture for developing intelligent financial assistants that can manage and performing a wide range of multi-step financial tasks, such as personalized financial planning, portfolio rebalancing, and account management, and we review the entire end- to-end workflow to build and deploy such autonomous systems. In particular, this work focuses on how large language models (LLMs) can be orchestrated with backend systems, services such as AWS Lambda, Amazon Bedrock, Agent Core Runtime for orchestration, and Amazon DynamoDB for state management, to enable autonomous financial services. We also address critical concerns related to security, ethical standards, and auditability, which are essential for responsible adoption of these systems in financial institutions. This research aims to bridge technological innovation with customer- centric and regulatory priorities in the finance industry. By doing so, this paper showcases how agentic AI can power next generation financial service delivery to transform customer experience and drive institutional efficiency.