Why Insurance Capacity Is Returning to California—and What It Will Take to Keep It There

California's homeowners insurance market is showing signs of recovery after three years of retreat. The California FAIR Plan added roughly 12,000 residential policies in Q2 2026, its fifth consecutive quarter of declining additions, down from more than 54,000 new policies in a single quarter at the peak in early 2025. Nine insurers, including six of California's 10 largest home insurance groups, have now committed to expand in the state.

Capacity is returning. The more important question is whether insurers now have the risk intelligence to make that capacity durable.

For carriers, that means being able to distinguish wildfire risk property by property, account for both wildland fire and urban conflagration, incorporate mitigation into risk decisions, and support those decisions with models that can withstand regulatory scrutiny.

ZestyAI Founder and CEO Attila Toth made the full argument for this recovery, and what it will take to sustain it, in a bylined viewpoint for Insurance Journal. Read Attila's perspective in Insurance Journal.

Here, we look more closely at the risk-modeling shift behind that recovery and what it could mean for catastrophe-exposed insurance markets beyond California.

Key takeaways

• California FAIR Plan residential additions fell from more than 54,000 per quarter at the early-2025 peak to roughly 12,000 in Q2 2026: five consecutive quarters of decline.
• Nine insurers, including six of California's 10 largest home insurance groups, have committed to expand in the state.
• More than 91% of the area burned in the January 2025 Eaton and Palisades fires had been rated High or Very High risk by ZestyAI's Z-FIRE™ before the fires occurred.
• Durable capacity depends on property-level, regulator-approved risk intelligence, not a return to the risk assumptions that failed before.

Is homeowners insurance capacity returning to California?

Yes. Several indicators suggest that California's homeowners insurance market is beginning to stabilize.

The clearest signal comes from the California FAIR Plan. Residential policy additions have now declined for five consecutive quarters, while commercial policies in force have fallen for two consecutive quarters. At the same time, major carriers are making commitments to expand their California books.

Travelers announced its expansion in April 2026. Farmers removed its policy cap in late 2025. Mercury committed to writing 38,000 new policies, including in distressed areas. The recovery is early and uneven, but the leading indicators, FAIR Plan additions, carrier commitments, actual policy counts, now point toward expansion rather than retreat.

Why did insurers pull back from California in the first place?

The pullback had been building for years. Major carriers had paused or restricted new homeowners business in California well before January 2025, after a decade of wildfire losses kept exceeding what their risk views had priced for.

The January 2025 Eaton and Palisades fires made the gap especially visible. The fires destroyed nearly 16,000 structures, took 31 lives, and produced roughly $40 billion in insured losses.

They also exposed a fundamental modeling challenge: wildfire risk is no longer only a wildland problem.

Eaton and Palisades became urban conflagration events, with fire spreading from structure to structure through dense residential areas. Risk models built primarily around vegetation, terrain, and historical wildfire boundaries can miss important elements of how fire propagates through the built environment.

For insurers, the consequence is straightforward. If the risk view does not adequately differentiate the properties most likely to experience loss, carriers have fewer tools to determine where they can responsibly write, how they should price risk, and where mitigation can meaningfully change an outcome.

Better insurance availability therefore depends in part on better risk selection.

What has changed in California wildfire risk modeling?

One of the most important changes is regulatory.

Under California Commissioner Ricardo Lara's Sustainable Insurance Strategy, insurers can now use forward-looking catastrophe models to inform catastrophe loads in rate filings, coupled with commitments to increase coverage in distressed areas.

That creates a path for carriers to base decisions on a more current and granular view of catastrophe risk rather than relying exclusively on historical loss experience.

California had already demonstrated that modern AI models could be incorporated into the regulatory process. ZestyAI's Z-FIRE™ became the first AI-powered wildfire model approved as part of a California carrier rate filing and has since been approved in additional carrier filings.

That regulatory history matters because sophisticated models are only useful to insurers if they can also be explained and defended.

A modern risk model must do more than produce a score. Carriers need to understand the factors influencing risk, reproduce results, document their methodology, and establish an audit trail that regulators and other stakeholders can evaluate.

Why does property-level wildfire risk matter?

Wildfire exposure can change dramatically from one property to the next, even within the same neighborhood.

Property characteristics such as roof condition, surrounding vegetation, defensible space, nearby structures, building density, topography, and other characteristics of the built and natural environment can influence how a property responds when a wildfire reaches a community.

Property-level models are designed to identify those differences rather than assigning the same broad risk view across an entire ZIP code, territory, or hazard zone.

That distinction becomes particularly important when insurers are trying to expand selectively into areas they previously considered too difficult to write.

With greater granularity, a carrier can identify properties where the underlying risk is more favorable, distinguish higher-risk structures from their neighbors, recognize mitigation, and make underwriting and pricing decisions at the level at which the risk actually exists.

What did Z-FIRE identify before the Eaton and Palisades fires?

ZestyAI's analysis of the Eaton and Palisades fire footprints illustrates what a property-level approach can reveal.

More than 91% of the area that ultimately burned had been classified as High or Very High risk by Z-FIRE before the fires occurred.

Within the burned area, properties in Z-FIRE's highest risk tier were roughly 50% more likely to be destroyed than properties in its lowest risk tier.

Those results matter for more than retrospective validation. They illustrate the kind of segmentation insurers need before an event occurs: a view of risk granular enough to differentiate individual properties and identify meaningful variation within the same catastrophe-exposed market.

How are insurers using property-level wildfire models in California?

Property-level wildfire intelligence is already being used across a significant share of the California market.

More than 40% of California homeowners premium is written by carriers using ZestyAI's view of wildfire risk. The California FAIR Plan uses Z-FIRE in its rating, and carriers are applying the model to support underwriting, rating, portfolio management, mitigation, and regulatory strategies.

New market entrants are also using property-level intelligence as part of their California strategy. Windward Risk Managers, DUAL North America, and Kingstone Companies are all underwriting California wildfire risk with Z-FIRE.

Windward Risk Managers, for example, entered the California homeowners market using Z-FIRE to evaluate wildfire risk at the individual-property level. Its expansion illustrates one way additional capacity can return: not by assuming that an entire distressed market has become less risky, but by identifying where risk can be understood and selected more precisely.

Only 11% of California homes fall into Z-FIRE's High Risk wildfire tier, and they are scattered through the same territories as everyone else. Territory-level rating and underwriting averages them together with their lower-risk neighbors. Property-level scoring separates them.

How can better wildfire models support insurance availability?

Better risk models cannot create capacity on their own. Rates, reinsurance, regulation, capital, claims experience, and market strategy all influence an insurer's willingness to write.

But risk intelligence affects nearly every one of those decisions.

A more precise view of risk can help insurers identify insurable properties within high-hazard markets, differentiate risk within a portfolio, recognize mitigation, communicate portfolio quality to reinsurers, and support rating and underwriting approaches with documented evidence.

This creates an alternative to the bluntest form of catastrophe management: withdrawing from entire territories because a carrier cannot confidently distinguish the risks within them.

For homeowners, that distinction can ultimately affect whether a property is considered writable at all.

What can other catastrophe-exposed states learn from California?

California may be the most visible example of the insurance industry adapting to changing catastrophe risk, but it is not the only market facing the problem.

Wildfire, severe convective storms, wind, hail, and other perils are creating similar pressure across the United States. As loss patterns change, insurers increasingly need risk views capable of differentiating exposure at the individual-property level rather than relying primarily on historical averages and broad geographic proxies.

The broader lesson from California is therefore not simply that capacity can come back after a period of retreat.

It is that sustainable capacity requires insurers to understand risk differently.

The models used to decide which properties to write, how to price them, how mitigation changes risk, and how portfolios will perform under future catastrophes have to keep pace with the risk itself.

California is beginning to test what that looks like in practice.

Frequently asked questions

What is Z-FIRE?

Z-FIRE™ is ZestyAI's AI-powered wildfire risk model. It scores wildfire risk at the individual property level for every address in the U.S., covering both wildland fire and urban conflagration. The model produces two scores: a neighborhood score that measures the likelihood a property will fall inside a future wildfire perimeter, and a property score that measures the likelihood the structure ignites, based on roof characteristics, defensible space, vegetation, topography, and surrounding building density. Z-FIRE is trained on the industry's largest wildfire loss database, spanning more than 2,000 fire events over 20 years, and incorporates the latest structure-ignition and materials research from the Insurance Institute for Business & Home Safety (IBHS). It outperforms traditional regional models by 44X in predicting property-level risk and is approved by regulators for rating and underwriting in every wildfire-prone state in the western U.S.

Is Z-FIRE approved for use in California?‍

Z-FIRE was the first AI-powered wildfire model approved as part of a California carrier rate filing and has subsequently been approved in additional carrier filings. ZestyAI's models have earned hundreds of regulatory approvals nationwide.

Does the California FAIR Plan use Z-FIRE?‍

Yes. The California FAIR Plan uses Z-FIRE as part of its rating approach to evaluate wildfire risk at the property level.

How is property-level wildfire modeling different from traditional wildfire hazard maps?‍

Traditional hazard views often classify risk across larger geographic areas based heavily on characteristics such as vegetation, terrain, and historical fire activity. Property-level models evaluate risk at the individual address and can incorporate characteristics of the structure, surrounding environment, nearby buildings, and mitigation to differentiate risk between neighboring properties.

Why are catastrophe models important to California's insurance recovery?‍

California insurers need to understand where they can responsibly expand while continuing to manage severe wildfire exposure. More granular, forward-looking catastrophe models can help carriers differentiate risk, recognize mitigation, manage portfolios, support regulatory filings, and identify properties that may be writable even within high-hazard areas.

A more precise path back into catastrophe-exposed markets

California's insurance recovery is still in its early stages. Rate filings still take time. Reinsurance capacity still matters. Another severe wildfire season could test the progress that has been made.

But the market is moving in a different direction than it was three years ago.

The next phase will depend not only on how much capacity returns, but on whether insurers have better tools for deciding where that capacity goes.

For California — and for every catastrophe-exposed insurance market watching it — more precise, property-level risk intelligence is increasingly becoming part of that answer.