This study examines how enterprise master data design can be operationalized as a primary mechanism for regulatory governance within highly regulated financial environments. The research addresses a persistent industry challenge where regulatory obligations such as OFAC screening, customer due diligence, and personal data protection are often implemented as isolated compliance processes rather than embedded into core data architectures. The purpose of this work is to demonstrate how governance-first master data management can translate regulatory intent into enforceable, auditable, and scalable enterprise controls. Using a qualitative case-based methodology grounded in architectural analysis, control mapping, and operating model assessment, the study evaluates how regulatory requirements are structurally realized through master data domains, stewardship workflows, validation checkpoints, and exception handling mechanisms. The findings show that treating master data as a governed control layer enables consistent regulatory enforcement across operational systems, reduces manual remediation cycles, and strengthens audit readiness. The study further highlights how clear ownership models, policy-driven data validation, and controlled synchronization patterns contribute to sustained compliance without constraining business operations. From an academic perspective, the research extends governance and information systems literature by positioning master data architecture as a regulatory execution instrument rather than a purely technical capability. From an industry standpoint, the study provides practical guidance for financial institutions seeking to embed compliance obligations directly into enterprise data foundations, reinforcing trust, transparency, and operational resilience.