Climate risk intelligence for pricing & actuarial

Price climate risk with evidence you can stand behind.

Use property- and portfolio-level models across flood, wildfire, hail, and extreme climate perils to sharpen segmentation, quantify potential loss, and support pricing assumptions.

In pricing & actuarial workflows

Price each risk for the exposure it carries.

Use science-backed climate intelligence, financial-loss metrics, and consistent model outputs to strengthen segmentation, rating, and actuarial analysis across your book.

Catch risks that history can blur.

Use property-level signals to distinguish locations with similar claims history but different physical exposure.

Connect perils to potential loss.

Compare exposure across all peril categories. For flood, go deeper with return-period depths and financial-loss outputs, including average annual loss (AAL), probable maximum loss (PML), and exceedance probability (EP) curves.

Apply the same risk logic across your book.

Bring scores and model outputs into quote, renewal, rating, and internal analytics workflows through the API or data delivery.

Your main model, or another view of the risk.

Use Geosapiens as your primary climate-risk model, or add it alongside existing models to compare outputs, test assumptions, and uncover meaningful differences in exposure.

Bring climate risk into your pricing workflow.

Start with sample locations or a portfolio slice. We'll show how Geosapiens differentiates the risks, what drives the results, and how the outputs can support pricing, segmentation, or model comparison.