This article presents a comprehensive framework for building resilient financial ecosystems through the integration of cloud-native architectures and artificial intelligence-driven risk management strategies. As financial institutions increasingly migrate to distributed computing environments, they face unprecedented challenges in maintaining operational resilience while addressing complex regulatory requirements. The article examines how the combination of microservices architecture, containerization, event-driven processing, and infrastructure as code can transform traditional banking systems, while AI methodologies enhance anomaly detection, predictive analytics, and regulatory compliance capabilities. Through analysis of implementation data from global financial institutions, the article demonstrates that this integrated approach yields significant improvements across key operational and security metrics. Recent industry data (2024–2025) shows that over 80% of global banks have adopted cloud-native and AI-driven risk management strategies, resulting in average operational cost reductions of 22–60% and measurable improvements in fraud detection, compliance, and system resilience. Continuous improvement and adaptation to evolving threats and regulations are now recognized as essential for sustainable financial resilience. The framework addresses critical security considerations through zero trust models, compliance-as-code principles, and secure DevOps practices, providing financial technology leaders with actionable insights for developing robust, adaptive financial systems capable of withstanding disruptions in an increasingly interconnected global economy.
S. Kohli (2025) studied this question.