(untitled) (International Journal of Engineering & Extended Technologies Research (IJEETR), 2024)
This paper presents an AI-driven, cyber-resilient architecture for SAP-based digital banking platforms deployed on AWS, designed to address the growing challenges of security, scalability, and operational efficiency in large-scale financial systems. The proposed architecture integrates real-time predictive intelligence and advanced analytics to proactively detect threats, anticipate system anomalies, and enhance cyber defense capabilities across SAP landscapes. Leveraging machine learning and deep learning models, the framework supports intelligent decision-making while enabling continuous monitoring and adaptive response to evolving risk scenarios. Automated cloud resource optimization mechanisms are incorporated to dynamically manage compute, storage, and network resources, ensuring high availability, cost efficiency, and performance resilience. The architecture also emphasizes cross-functional integration across security, cloud operations, and business teams, supporting multi-year digital transformation initiatives. By transitioning from traditional perimeter-based protection to an intelligent, predictive cyber defense model, the proposed approach demonstrates significant impact on the reliability, security, and scalability of modern digital banking ecosystems.