Financial institutions today face a dual challenge: rapidly evolving regulatory requirements and growing expectations for transparency and accountability. Traditional compliance systems, reliant on siloed data warehouses and manual processes, often fail to deliver timely insights or ensure auditability. This paper introduces a management framework for Cognitive Data Pipelines (CDPs), which integrate artificial intelligence, modular architectures, and transparent analytics to address compliance challenges in financial services. Drawing on a case illustration from a multinational bank, the study demonstrates how CDPs reduced reporting cycles by 67%, cut error rates by 40%, and lowered compliance incidents by half. The framework consists of four interdependent layers: data ingestion and quality, cognitive processing, governance and explainability, and managerial insight. Implementation challenges include skill gaps, cultural resistance, and legacy system integration. The paper discusses adoption strategies, governance considerations, and return-on-investment implications, offering managers a practical roadmap for compliance modernization in highly regulated environments.