Agentic AI for Secure Financial Data Processing: Real-Time Analytics, Cloud Migration, and Risk Mitigation in AWS-Based Architectures
Rohit Kumar · International Journal of Innovative Research in Science Engineering and Technology · 2025
Using Agentic AI in concert with AWS Full Stack Development, this study offers a technically solid and scalable method to securely process financial data. AWS Lambda for serverless computation, Amazon S3 for scalable storage, AWS Glue for data classification and transformation, Athena for SQL-like querying, and QuickSight for interactive visualisation comprise the fundamental elements of the system. While Agentic AI modules enable autonomous decision-making abilities to regulate data integrity, recognise abnormalities, and adaptably react to compliance violations, Custom AWS configuration rules are used for real-time compliance monitoring. Tight guidelines like PCI-DSS and GDPR enable secure cloud migration, improved auditability, and policy execution. These guidelines open the path for real-time, low-latency analytics on enormous financial data. Combining data-driven insight production with intelligent control will help to build a transparent and strong environment fit for modern financial activities, as the suggested approach shows.