Advancing Data Integrity in Banking: AI/ML Solutions and Best Practices

Abstract

The accelerating integration of Artificial Intelligence (AI) and Machine Learning (ML) into banking operations has ushered in transformative possibilities, but also necessitates unwavering attention to data integrity. This paper explores how AI/ML-driven innovations can be harnessed to enhance data integrity within the banking sector. By presenting a comprehensive framework that amalgamates AI/ML technologies with best practices for data integrity, this study offers a roadmap for banks to fortify their data governance strategies and ensure the accuracy, reliability, and compliance of their AI/ML initiatives. Through the exploration of real-world case studies, regulatory compliance considerations, and ethical implications, this paper unveils the symbiotic relationship between AI/ML solutions and data integrity, providing insights that enable banks to navigate the complex landscape of modern banking with confidence.