The Role Of AI In Strengthening Data Privacy For Cloud Banking

Abstract

The rapid adoption of cloud banking has transformed the financial sector by enhancing efficiency, scalability, and accessibility. However, this shift has introduced significant data privacy and cybersecurity challenges, as sensitive financial information becomes increasingly vulnerable to breaches, unauthorized access, and regulatory non-compliance. Artificial Intelligence (AI) has emerged as a powerful solution to address these challenges, offering advanced tools for real-time threat detection, anomaly monitoring, and privacy preservation. This study systematically reviews 62 peer-reviewed articles using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to explore the role of AI in strengthening data privacy within cloud banking systems. The findings reveal that AI-driven models, including machine learning, deep learning, and federated learning, improve threat detection accuracy, reduce false positives by up to 65%, and enable secure, multi-institutional collaboration without exposing sensitive information. Furthermore, AI enhances compliance automation, ensuring adherence to regulatory standards such as GDPR and CCPA while improving reporting efficiency by 50%. Despite challenges such as algorithmic biases and the resource-intensive nature of AI systems, advancements in adversarial training and explainable AI offer promising solutions.