intelligence × insurance

Decision intelligence for Insurance.

Score loss, price, and fraud on live policy and claims data, and forecast reserves before they develop — so underwriting, claims, and actuarial work from the same forward view instead of a quarter-old triangle.

Loss & risk scoring Claims fraud detection Reserve forecasting

Underwriting and reserving on a forward view

Insurance runs on estimates of the future, yet most carriers manage them with backward-looking tools. Loss ratios are read after the period closes, fraud is caught in audit rather than at first notice, and reserves are set from triangles that lag emerging development by months. The result is rate that is wrong before anyone notices and surprises that land at quarter-end.

Decision intelligence brings prediction to the point of decision. We build models on your policy admin, claims, and billing systems that score loss and risk at quote, flag pricing inadequacy as the book drifts, detect fraud at first notice of loss, and project reserve development from claim characteristics. Underwriters, adjusters, and actuaries act on signals early enough to change the outcome.

Three layers of insurance decision intelligence.

Portfolio reporting, predictive models, and live signal on one governed view of policy and claims data.

01 / reportingCORE
BI on insurance operational data
Live views of loss ratio, written and earned premium, and portfolio mix — built on policy admin and claims data instead of month-end bordereaux.
  • Loss ratio by segment and peril
  • Premium and exposure tracking
  • Portfolio concentration views
02 / predictionCORE
Predictive loss & reserve models
Loss and risk scoring at the point of quote plus reserve development forecasting, so pricing and IBNR rest on prediction rather than lagging triangles.
  • Expected-loss and risk scoring
  • Pricing-adequacy signal
  • Reserve development forecasts
03 / detectionSECURE
Real-time claims fraud signal
Streaming fraud scoring on incoming claims that routes suspicious files to SIU at first notice of loss with the indicators that triggered the flag.
  • First-notice fraud scoring
  • Network and pattern detection
  • SIU-in-the-loop review

Decisions worth instrumenting in Insurance

The models that earn their place are the ones an underwriter, adjuster, or actuary can act on before the loss is locked in:

  • Loss and risk scoring — rate each risk against expected loss at quote and renewal so underwriters bind on evidence, not on a desk rate that lags the exposure.
  • Pricing signal — surface where rate is inadequate and where the portfolio is drifting into unprofitable segments early enough to correct it.
  • Claims fraud detection — score files at first notice of loss to route suspicious claims to SIU before payment and reduce leakage.
  • Reserve forecasting — project ultimate development from claim-level characteristics so reserving teams set IBNR with fewer quarter-end surprises.

Common questions.

How does decision intelligence improve loss and risk scoring in underwriting?

We score expected loss and risk at the point of quote and renewal from exposure data, prior claims, and external signals, so underwriters see how a risk compares to the book before binding. Pricing signal surfaces where rate is inadequate or where the portfolio is drifting into unprofitable segments while there is still time to correct.

Can you detect claims fraud and forecast reserves with predictive models?

Yes. We score incoming claims for fraud indicators in real time so suspicious files are routed to SIU early, and we forecast reserve development from claim characteristics and historical patterns so reserving teams can set and adjust IBNR with more confidence and fewer surprises at close.

Explore related capabilities.

Catch the loss before it develops.

Thirty-minute briefing for underwriting, claims, and actuarial leadership. We map where predictive scoring changes the call and leave you with a roadmap and ROI memo. Response inside 24 hours.