{% endcolumn %}
{% endcolumns %}
## 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](/climate-resilience-suite/climate-risk-and-resilience-index.md) 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.
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](/adaptation-data-hub/methodology-2-3-global-adaptation-layer.md) 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.
---
# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.alphageo.ai/adaptation-data-hub/alphageo-for-insurance.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.