Data Warehousing for BFSI: Modeled for Risk, Reconciled to the Ledger

A regional bank starts a data warehouse modernization. Two and a half years later, the warehouse is technically live but the risk team still runs its analytics off the old finance data mart, the regulatory reporting team still pulls from the legacy reporting system, and the new warehouse is mostly used for ad-hoc analytics that nobody trusts for decisions. The reasons are familiar: the dimensional model wasn't designed against the real questions the business asks, the reconciliation to the GL was treated as a future-phase activity that never happened, the slowly-changing dimensions for products and accounts produce surprising answers when examined closely, and the lineage documentation was never produced because nobody owned it. Each of these is fixable. Together they produce a warehouse that exists technically but doesn't earn trust as the source of truth.

BFSI data warehousing done right starts with the dimensional model and the actual questions, not the technology choice. Customer, account, product, position, and event facts at the right grain. SCD-2 for products and customer attributes that change over time. Conformed metrics that match how finance and risk define them. Reconciliation to the GL and risk system of record, run continuously and surfaced when variances appear. Lineage documentation that supports any examination question. With these in place, the warehouse earns trust over the first six months and becomes the institution's source of truth. Without them, it becomes a parallel system that doesn't displace the legacy environment it was supposed to replace.