AI-Based Data Analytics for Financial Risk Governance and Integrity-Assured Cybersecurity in Cloud-Based Healthcare

Abstract

The rapid adoption of cloud computing in financial and healthcare sectors has enabled large-scale data analytics, improved decision-making, and enhanced operational efficiency. However, it introduces critical cybersecurity risks, including data breaches, fraud, and compliance challenges. This paper proposes an AI-Driven Analytics framework for Secure, Reliable, and Integrity-Assured Financial and Healthcare Cybersecurity in the Cloud, designed to address these challenges effectively. The framework leverages advanced AI algorithms and analytics to detect anomalies, predict potential cyber threats, and provide actionable insights while ensuring data integrity and system reliability. Cloud-native security mechanisms, including encryption, access control, and compliance monitoring, are integrated to adhere to regulatory standards such as HIPAA, PCI-DSS, and GDPR. Experimental evaluation demonstrates improved threat detection accuracy, enhanced system reliability, and robust protection for sensitive financial and healthcare data. This approach provides a comprehensive, secure, and trustworthy foundation for managing cybersecurity risks in cloud environments.