AI-Powered Cloud Architecture for Secure Real-Time Financial Analytics in Banking and Healthcare

Abstract

The increasing digitalization of banking and healthcare systems has generated massive volumes of financial and operational data that require real-time analytics for effective decision-making. While cloud computing enables scalable and cost-efficient data processing, it also introduces critical challenges related to security, privacy, and regulatory compliance. This paper proposes an AI-Powered Cloud Architecture for Secure Real-Time Financial Analytics in Banking and Healthcare, designed to deliver intelligent, scalable, and cyber-resilient analytics capabilities. The proposed architecture integrates cloud-native services with advanced AI and machine learning models to support real-time data ingestion, predictive analytics, and anomaly detection. Security is embedded across all architectural layers through encryption, role-based access control, continuous monitoring, and compliance enforcement aligned with standards such as PCI-DSS, HIPAA, and GDPR. Experimental evaluation demonstrates improved analytical accuracy, low-latency processing, and enhanced protection against financial fraud and cyber threats. The results indicate that the proposed solution effectively supports secure, real-time financial analytics while maintaining data integrity and system reliability in cloud-based banking and healthcare environments.