Exposure data connected to catastrophe models, answered in plain language.
Connect exposure data to established catastrophe models to assess disaster scenarios, potential losses, and portfolio concentrations.
- Industry
- Insurance & reinsurance · Insurers and reinsurers
- Category
- Catastrophe & portfolio risk
- Buyer
- Chief underwriting officer, head of reinsurance, or exposure management lead
- Deployment
- Private cloud or on-premises, alongside your licensed catastrophe models
Scenario questions take days, because the data and the models live in different places.
Exposure data arrives in schedules and bordereaux of every shape. Before a catastrophe model can run, someone has to clean, map, and load it, and every new scenario question from underwriting or reinsurance joins a queue.
That slows renewals and leaves concentrations harder to see than they should be, especially when an event is unfolding and the business needs an answer quickly.
From your data to a decision a person can check.
- 01
Prepare
Language models read and map exposure schedules into the formats your catastrophe engines expect, with every mapping reviewable.
- 02
Model
Losses are estimated by established catastrophe engines and licensed data. The language model coordinates the run; it does not estimate losses.
- 03
Explore
Underwriters and reinsurance teams ask scenario and concentration questions and get answers grounded in the model outputs.
- 04
Report
Results are assembled into exposure and concentration views ready for underwriting and reinsurance decisions.
Target outcomes for a first deployment.
Targets based on comparable workflows. Each one is confirmed against your own baseline during the pilot.
- Faster exposure analysis
- Better-supported underwriting decisions
- Better-supported reinsurance decisions
- Loss estimates come only from established catastrophe models
- Data mappings reviewable before any run
- Every answer linked to the model run that produced it
One workflow, measured against your baseline.
One portfolio and one peril region, using your existing catastrophe model licence.
- 01Time from exposure data to model-ready input
- 02Time to answer a scenario question
- 03Mapping accuracy against manual preparation