The new gold rush? How to unlock the “uninsurable” market
Overview
Insurers can find opportunity in previously off-limits, high-risk regions through:
- Climate risk analytics: A new framework using precision data and AI to assess hyper-local risk and uncover vulnerabilities traditional models miss.
- Modern catastrophe risk modeling: Solutions that shift the focus away from historical averages to property-level precision.
- A forward focus: Using AI to identify emerging risks—like the wildfire-to-flood cycle—to price risk accurately.
A new gold rush is on the horizon for insurers, but it’s not for precious metals or oil. It’s for the data that will unlock a massive, untapped market: the millions of properties in high-risk regions that so many providers have deemed “uninsurable.”
For years, property and casualty (P&C) insurers have been in full retreat from these areas, leaving a massive market gap. As a result, California’s FAIR Plan has swelled to more than 452,000 policies.
While this may seem like a risk crisis, it is actually a symptom of outdated catastrophe risk modeling across the industry. By shifting from traditional underwriting to a strategic, predictive framework, insurers can turn a coverage crisis into a frontier of growth.
What does traditional property insurance underwriting involve?
Traditionally, underwriting involves evaluating risk based on historical data, broad geographic classifications, and static hazard maps. This approach relies on analyzing past events—such as the frequency of fires or floods in a specific zip code over the last 50 years—to predict future losses.
Traditional underwriting often treats all homes within a certain radius as having the same risk profile. It doesn’t take into consideration unique structural characteristics or individual mitigation efforts.
What are the problems with traditional property insurance underwriting?
Traditional underwriting is failing because it operates on the outdated assumption that the future will look like the past.
To move forward, risk modeling must now account for:
- Interdependent risks: Hazards beget other hazards. For example, vegetation growth from wet winters fueled the $40 billion Los Angeles wildfires of 2025. Then those burn areas have created conditions for catastrophic floods.
- The expanding Wildland Urban Interface (WUI): There are now roughly 45 million U.S. residences now in the WUI (the area where human-built structures and infrastructure meet or intermingle with undeveloped wildland and vegetative fuels), leading to fires that have tripled in size.
- New geographic risks: Events like the Central Texas flash floods of July 2025—a 1,000-year rainfall event—devastated communities that traditional maps didn’t show as risky.
How can insurers unlock the “uninsurable” market?
The key to unlocking the “uninsurable” market is using climate risk analytics to reveal the true, hyper-local risk profile of every single property. Even in the same neighborhood, ten houses can have vastly different risk levels based on specific structural characteristics.
Cotality offers Climate Risk Analytics (CRA)—advanced solutions that integrate high-resolution climate modeling with property data. These insights are powered by our Climate-Coupled-Catastrophe Models™ (C3 Models™), the next generation of catastrophe risk modeling.
These solutions enable insurers to:
- Pinpoint hidden vulnerabilities: Our models evaluate all the nuances of risk. For example, our analysis of the 2025 Los Angeles fires revealed that 75% of properties within the Eaton fire perimeter—initially rated as low-to-moderate hazard—actually faced high conflagration risk.
- Project future risk: Our models project future risk based on best-in-class climate science. We integrate Intergovernmental Panel on Climate Change (IPCC) scenarios to assess environmental impacts on a property 30 years into the future.
- Quantify peril interdependencies: Our catastrophe risk modeling reveals all the risks associated with a unique address. They provide a holistic view of the wildfire-to-flood cycle.
How does Climate Risk Analytics support profitability?
Cotality’s climate risk analytics solutions provide a data-driven framework for determining when environmental risk can still yield a revenue stream. Key insurance use cases include:
- Accurate, risk-based pricing: Our Composite Risk Score (CRS) streamlines more than 20 detailed risk measures into a single metric, allowing carriers to differentiate between a vulnerable home and a resilient home within the same zip code.
- Innovative product design: Data-driven insights allow carriers to offer policies with discounts for specific mitigation, such as fire-resistant roofing or defensible space.
- Proactive portfolio management: Carriers can use our data to actively manage their portfolios, identifying high-risk assets that need targeted mitigation or re-evaluation. Managing a book of business becomes a strategic exercise in risk reduction and long-term health.
Re-engaging the “uninsurable” market
Ignoring the “uninsurable” market is no longer a viable business, nor is it a sustainable strategy for building resilience.
By leveraging Cotality's intelligence, P&C insurers can stop retreating and start innovating. It’s time to pursue a gold rush with a robust catastrophe risk modeling framework that turns a seemingly impossible market into a profitable frontier.
Ready to turn environmental challenges into opportunities? Check out our webinar, ‘Making the shift: How to turn environmental risk into a strategic advantage.’