The accelerating digitization of global Banking, Financial Services, and Insurance (BFSI) operations has amplified the demand for compliance-driven data platforms that can unify heterogeneous risk data across jurisdictions while adhering to stringent regulatory regimes such as GDPR, PCI-DSS, and Basel III. This study presents the design and evaluation of a federated compliance data platform that integrates multi-region Snowflake warehousing with a distributed governance framework to enable cross-border risk analytics at scale. Using a hybrid deployment spanning North America, EMEA, and APAC regions, the platform ingests over 12 TB/day of structured and semi-structured financial datasets, harmonized across 48 regulatory taxonomies. A federated governance layer—anchored in policy-as-code, lineage-aware data catalogs, and region-specific encryption keys—was implemented to enforce jurisdictional controls while preserving analytic interoperability. Benchmarking results indicate a 41% reduction in data reconciliation latency and a 32% improvement in compliance audit readiness compared to traditional monolithic data lakehouse models. Furthermore, federated query execution across Snowflake regions demonstrated sub-250ms latency for 85% of analytic workloads, supporting real-time liquidity risk and anti-money laundering (AML) monitoring. The findings underscore that multi-region, federated data architectures not only achieve regulatory alignment but also deliver measurable performance and risk management gains for globally distributed BFSI enterprises.
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