Data Lineage and Metadata in Payment Ecosystems: Auditability and Regulatory Readiness across the Life Cycle

Abstract

Current payment ecosystems create data at high velocity, in small granularity, that needs to satisfy significantly higher regulatory demands in the areas of transparency, auditability, and operational assurance. Nevertheless, the column-level transformations, defining data-handling policies, and timely visibility of legacy metadata platforms and fixed documentation practice are not provided during the audits and regulatory assessments. In the given paper the authors suggest an active metadata-based platform that provides end-to-end, column-based data lineage, between ingestion and reporting, which allows behind-real-time governance of the payment data life cycle. The framework incorporates policy-as-code to automate policy access-control, retention rules and segregation-of-duty checks to do away with manual governance steps and promote uniform enforcement between policy-cycles. They include impact analysis features to measure the downstream impact of schema or logic modification to reduce operational and compliance risks associated with changes to a significant degree. The lineage objects are mapped to a unified business glossary containing the standardized definitions throughout systems as well as enhancing traceability to auditors and regulators. The results of implementation show that measurable improvements can be observed, such as a reduction in the number of audit results, the shortening of the regulation response cycle, and the increase in control evidence because verifiable lineage screenshots and metadata artifacts are generated. The work adds a scalable architecture and validation procedure to attain audit-ready, regulator-congruous information management in the contemporary pay surroundings.