Use Case: Insurance Risk Models and Underwriting

Integrate resilience into underwriting and guide clients towards adaptation

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Integrate resilience into underwriting

Insurers already model physical hazard well. The next step is to model how local adaptation changes likely loss.

AlphaGeo’s Global Adaptation Layer helps insurers enhance their own physical climate risk models with hazard-specific resilience data. This makes it possible to assess physical climate risk (undefended) and resilience-adjusted risk (defended) side-by-side for more precise underwriting and pricing.

Why adaptation data matters for insurers

Two properties can face the same physical hazard but very different outcomes. The difference often comes from local adaptation capacity and asset-level resilience.

That gap matters for underwriting. A model that only captures hazard intensity can miss where defenses, drainage, building strength, or response capacity reduce likely damage.

Model unmitigated and mitigated risk together

AlphaGeo’s Climate Risk and Resilience Index shows how physical risk changes once adaptation is included.

This dual view helps insurers:

• benchmark baseline hazard exposure against mitigated risk

• identify pockets of resilience inside high-risk markets

• improve pricing precision without losing hazard transparency

The California wildfire example below shows how resilience-adjusted scoring can reveal relatively safer locations inside a high-risk state.

Figure 2: Resilience-adjusted risk highlights locations where adaptation reduces likely damage.

Underlying hazard drivers remain fully visible. This lets insurers compare the physical signal with the resilience signal rather than replacing one with the other.

Global Adaptation Layer for underwriting models

The Global Adaptation Layer is a hazard-specific dataset of local adaptation capacity. It covers more than 20 engineered and nature-based adaptation measures worldwide.

These layers can be used directly in insurer workflows to strengthen internal view-of-risk models. They help quantify whether a location is protected by features such as flood defenses, drainage infrastructure, fire response capacity, natural buffers, or stronger building stock.

What this enables

With AlphaGeo, insurers can:

1. Enhance internal peril models with local adaptation variables.

2. Model unmitigated and mitigated risk in parallel.

3. Support more precise underwriting at quote, renewal, and portfolio level.

This supports decisions such as:

• refining technical pricing in exposed geographies

• differentiating resilient properties from lookalike risks

• guiding policyholders toward targeted remediation

From risk selection to resilience incentives

Adaptation data is useful beyond risk selection. It also helps insurers design products and engagement strategies that reward resilience. With precise data quantifying adaptation capacity, underwriters can identify adaptation gaps, support targeted loss prevention, and track how mitigation measures may improve risk quality over time.

This creates a clearer path to resilience-linked pricing, and stronger retention in climate-exposed markets.