Data Engineering for Insurance: Pipelines That Reconcile to the Statutory Close

A SaaS data pipeline ingests JSON from APIs and writes to a warehouse. An insurance data pipeline has to ingest policy events from Guidewire PolicyCenter, claim transactions from ClaimCenter, billing events from BillingCenter, general ledger entries from SAP or Oracle, reinsurance bordereaux from MGAs, and bureau loss costs from ISO and NCCI — and every one of those streams has to reconcile to the statutory close at the end of the month. Premium written reconciles to the GL. Losses paid reconciles to the GL. IBNR allocations reconcile to the appointed actuary's reserves. Reinsurance ceded reconciles to the treaty terms. When the pipeline doesn't reconcile, finance loses trust in the warehouse and goes back to the manual process. Every insurance data engineering project that has ever failed has failed for this reason.

Insurance data engineering done right uses the medallion pattern (bronze raw, silver curated, gold business-ready) — but with extras: accident-year and underwriting-year dimensions baked into silver, premium earning patterns calculated correctly, IBNR allocation logic applied consistently, slowly-changing dimensions for endorsements and policy versions, and reconciliation reports that run after every load and surface variances against the GL before anyone trusts the gold layer for analytics. With those in place, the pipeline becomes the single source of truth that finance, actuarial, and operations can all defend.