CLOUD-NATIVE ARCHITECTURES IN FINANCIAL SERVICES: A COMPREHENSIVE ANALYSIS OF AI WORKLOAD SCALING AND FRAUD DETECTION

Abstract

This comprehensive article examines the transformative impact of cloud-native architectures in the financial services sector, particularly focusing on AI workload scaling and fraud detection capabilities. The article explores the evolution of cloud adoption in banking, analyzing various aspects including data integration architectures, AI model deployment strategies, and operational components. The article investigates how financial institutions have leveraged containerization, machine learning, and Kubernetes orchestration to enhance their security posture and operational efficiency. Through detailed analysis of real-time alert systems and compliance frameworks, the article demonstrates significant improvements in fraud detection, regulatory compliance, and overall business performance. The article highlights the crucial role of cloud-native approaches in modernizing financial services infrastructure while maintaining robust security controls and regulatory compliance.