Insurance data analytics for P&C, life, and health carriers. Unified claims data, automated regulatory reporting, and a metric layer actuaries trust.
How do you handle data from multiple legacy policy administration systems?
We build a unified data layer that normalizes and reconciles data from multiple source systems without requiring a platform replacement. We map each source to a common semantic model and document the lineage so every number is traceable to its origin.
Yes. We build automated pipelines that produce regulatory outputs directly from your certified data layer. This eliminates the manual reconciliation that typically consumes weeks of actuarial and finance team time before each filing cycle.
Most insurance data foundation engagements run 12 to 16 weeks. We start with a 30-day Analytics Truth Audit that maps your current data landscape and identifies the highest-priority gaps before any build work begins.
We work with both. The data structures differ significantly between lines of business, but the underlying governance and metric layer challenges are consistent. We have experience with personal lines, commercial lines, specialty, and health insurance data environments.
Insurance data analytics consulting for P&C, life, and health carriers. Unify claims data, automate regulatory reporting, and build trusted metrics.
Data analytics for insurance carriers and MGAs. Claims, underwriting, and risk metrics.
Insurance companies sit on decades of claims, underwriting, and policyholder data that is rarely unified or governed. We build the metric layer that makes regulatory reporting, loss ratio analysis, and AI-driven underwriting possible.
Insurance data work that holds up under regulatory scrutiny.
Start with a 30-day Analytics Truth Audit. We identify exactly what is broken and give you a 90-day roadmap to fix it.