Building Trust in Banking AI/ML through Data Governance and Integrity

Abstract

The rapid integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies within the banking sector has sparked a transformational wave of innovation. However, this transformation hinges on the foundation of trust, especially concerning the accuracy, security, and ethical usage of customer data. This paper delves into the critical role of data governance and integrity in building and maintaining trust in AI/ML-powered banking. Through an exploration of best practices, frameworks, and real-world case studies, this study demonstrates how robust data governance and data integrity measures bolster transparency, accountability, and compliance, thereby establishing a trustworthy environment for the deployment of AI/ML technologies in banking.