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ZestyAI’s AI-Powered Wildfire Risk Model Available for Immediate Use in California Rate Filings

ZestyAI’s Z-FIRE™ Continues to Support California Insurers Amid Regulatory Changes.

ZestyAI, the leader in AI-powered climate and property risk analytics, announced that Z-FIRE™, its advanced wildfire risk model, is filing-ready in California.

Z-FIRE can continue to be filed for rate segmentation and underwriting without further review under the Pre-Application Required Information Determination (PRID) process, which is currently focused on models that determine a catastrophe load factor.

Z-FIRE was last included in an approved California rate filing in 2024.

Z-FIRE leverages AI-driven analysis of over 2,000 historical wildfires, integrating satellite and aerial imagery, topography, and property-level characteristics to provide precise risk assessments. This approach is rooted in decades of science and experimentation by researchers, including the Insurance Institute for Business & Home Safety (IBHS).

With coverage spanning nearly 100% of U.S. properties, Z-FIRE is already trusted by more than one-third of California’s insurance market, including the California FAIR Plan, the state's insurer of last resort, to refine underwriting, enhance risk segmentation, and ensure that premiums accurately reflect the true wildfire exposure and vulnerability of each individual structure.

"For years, leading insurers have trusted ZestyAI to manage wildfire exposure in California and refine pricing segmentation with precision," said Attila Toth, Founder and CEO of ZestyAI. "Now, insurers can continue to confidently integrate it into their rate filings."

They can trust that Z-FIRE meets the highest actuarial and scientific standards, ensuring transparency and reliability for regulators, carriers, and policyholders alike.


ZestyAI continuously validates Z-FIRE’s performance through post-event analyses, assessing how well its risk designations align with real-world fire impacts.

Following the recent Los Angeles wildfires, preliminary analysis indicates that Z-FIRE’s highest-risk ratings closely correspond with the hardest-hit areas, with 94% and 87% of the areas affected by the Palisades and Eaton fires rated as high or very high risk by the model.

The model also captured how property-specific characteristics influenced damage patterns, even within the same fire perimeter, reinforcing the importance of granular, structure-level insights in wildfire risk assessment. Z-FIRE’s data also reveals more than 1.5 million structures in California face a high or very high risk of being within a wildfire perimeter.

With granular, property-specific insights, Z-FIRE allows insurers to move beyond binary "insure or drop" decisions. Instead, they can work with policyholders to reduce vulnerability—whether through defensible space measures, fire-resistant roofing, or other mitigation efforts.

Since its adoption, Z-FIRE has helped insurers confidently write hundreds of thousands of policies that might have otherwise been non-renewed or declined. By incorporating vegetation density, roof materials, and structural characteristics, the model enhances risk segmentation, reduces volatility, and strengthens market stability.

ZestyAI has engaged with the California Department of Insurance (CDI) over the years, including discussions during the early regulatory considerations of Z-FIRE. After an independent actuarial review in 2020, multiple carrier rate and underwriting filings leveraging Z-FIRE have been approved by the CDI. Moreover, ZestyAI participated in seven CDI workshops in 2023-24 and co-hosted a January 2025 webinar on the new regulatory framework.

Research

AI in Insurance: How to Stay Ahead of the Curve

Artificial intelligence is reshaping the P&C insurance industry, offering new ways to streamline underwriting, enhance risk management, and navigate evolving regulations.

But as AI adoption accelerates, insurers must ensure they’re using these technologies effectively—balancing innovation with compliance.

Our latest guide explores the most impactful AI applications in insurance, including:

  • AI-powered underwriting and predictive analytics
  • How regulators are shaping the future of AI in insurance
  • Best practices for integrating AI while ensuring fairness and transparency
As AI-driven tools become the new standard, insurers who adapt early will gain a competitive edge.

Download our free guide to leverage these innovations while staying aligned with evolving regulations.

Research

The Truth About Roof Age: 5 Critical Insights Every Insurer Should Know

For insurers, accurate roof age data is essential. Yet, self-reported information often falls short.

Our research shows that 1 in 5 homeowners underreport roof age by an average of 8 years. These discrepancies create hidden risks that can impact underwriting, pricing, and overall portfolio performance.

How can insurers get a more accurate picture?

AI-driven insights provide 97% nationwide coverage, combining verified roof age with real-time condition data for a more comprehensive risk assessment.

Download our latest research for a breakdown of five critical insights that every insurer should know about roof age. 

Plus, get access to The Roof Age Advantage, an exclusive video that unveils how AI is setting a new standard for risk evaluation.

Blog

Merging Centuries of Expertise with AI for a New Era of Risk Assessment

In 2024, U.S. insured catastrophe losses soared to $113 billion. Learn how we combine centuries of insurance expertise with AI to help insurers navigate an increasingly volatile climate.

                           The property and casualty (P&C) insurance industry has always been about protecting people and property against the unexpected. But in 2024, U.S. insured catastrophe losses reached $113 billion—nearly double the 25-year average of $58 billion.

For many carriers, the gap between collected premiums and total payouts, including operating costs, continues to widen, underscoring the growing financial strain of climate-driven risks. At ZestyAI, we can’t control the forces of nature, but we’re helping insurers adapt.

                       

From Franklin’s Fire Policies to AI-Powered Resilience

The concept of insurance dates back to the Middle Ages, when merchants sought protection from unpredictable events like storms and piracy. Over time, the practice evolved into today’s property and casualty insurance, safeguarding homes, businesses, and communities.

In the United States, Benjamin Franklin advanced the industry by founding the nation’s first fire insurance company in 1752. By refusing to insure fire-prone buildings, his company not only mitigated risk but also set new safety standards. This principle of risk reduction has guided the industry ever since.

Today, ZestyAI is building on that foundation with AI-driven risk models that help insurers address modern challenges. While the tools have changed, the mission remains the same: to protect people, property, and the future.

Modern Tools for Today’s Challenges

At ZestyAI, we’re helping insurers address modern challenges with solutions designed to fit seamlessly into their workflows. Our AI-driven platform combines high-resolution aerial imagery, proprietary data, and advanced modeling to provide a clearer, more reliable view of risk.

Unlike broad, traditional approaches, we focus on delivering actionable insights at the property level, helping insurers:

  • Modernize outdated processes without overhauling their systems,
  • Improve underwriting precision,
  • Optimize inspections and resources, and
  • Strengthen their portfolios.

A key example of this is our work in wildfire risk modeling. ZestyAI’s proprietary wildfire loss database—built using data from 1,500 events over the last 20 years—helps insurers predict property-specific risks with precision. By understanding wildfire risk at this granular level, insurers can proactively reduce losses, guide mitigation strategies, and protect their customers with greater confidence.

Discover how ZestyAI’s regulator-approved solutions set new standards for accuracy, compliance, and fairness in insurance.

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