Non-Admitted (E&S): Bind-ready pricing under E&S speed

Quote E&S with conviction

From data to deployed rater, Tesora can help every step. Anomaly detection, curve fitting, SOX compliance, API deployment.

Making AI trustworthy for E&S actuaries

While actuaries can use mainstream AI on narrow tasks, they can't streamline the workflows with AI yet, until now. Tesora brings actuarial rigor in the form of transparency and reproducibility, all with AI that is trained in actuarial science.

From messy data to auditable rates

Tesora puts the power back in the actuary's hands to manage their models, by handling the workflow and IT compliance burden that normally slows a new product launch to a crawl. New product to quote in 1 week, not 3 months.

The audit pack the chief actuary signs against.

Every bound quote ships with a per-policy audit pack. Not a one-line price. A walkable trail from the broker submission all the way down to the cell of the rater that produced each multiplier.

The lines that don't fit a textbook.

Hard-to-rate exposures, multi-class programs, and chief actuaries who own the rate plan end to end.

Two agents carry the specialty desk.

Admitted carrier instead?

Messy, sparse data

Thin claims data, anomaly detection, and unstructured inputs normalized to one table the actuary can work from.

New product setup

Stand up a new program with the rate plan, curves, and credibility weights the actuary chooses.

Rater build

Build a versioned rater in the Workbench and deploy it in hours.

Audit and dual-control

Author, reviewer, and approver are separate people, and every promotion between them is recorded.

Callable API

The same rater that signs off in dev runs in production behind your binding pipeline.

Rating Agent

Submission to bindable quote.

Read the broker submission, build the rater, return a quote with the per-credit citation trail attached. Old versions stay live so historical quotes reproduce exactly.

Insight Agent

Loss data into priced risk.

Normalize loss runs across the insured's history, fit class-level severity, and feed the rater with credit factors traced back to the source.