Data Governance Evolution: Enabling AI/ML Innovations in Banking

Abstract

As the banking industry continues to integrate AI/ML technologies into its operations, the evolution of data governance emerges as a pivotal enabler. This paper explores the dynamic landscape of data governance in the context of AI/ML innovations in banking. We delve into the essential components of effective data governance, including data quality, privacy, security, and compliance. Through a comprehensive review of literature and case studies, we analyze the challenges and opportunities presented by AI/ML adoption within the framework of evolving data governance practices. By highlighting the critical role of data governance in ensuring the ethical and responsible use of AI/ML, this paper provides insights into how banks can navigate the intricacies of data management to drive innovation while safeguarding customer trust and regulatory adherence.