From Costly Water Losses to Millions in Savings

Non-weather water claims are a leading cause of property insurance losses, costing insurers over $20 billion annually. 

Join us for a FREE live webinar where our experts will discuss the latest trends, challenges, and insights to help you mitigate non-weather water risk.

What We'll Cover

Our experts Rob Silva, ACAS (Director of Customer Success) & Sam Fetchero (Head of Marketing) will present:

• Current Trends: Understand the rise in severity and total loss costs of non-weather water claims.
• Risk Assessment Challenges: Learn why traditional methods fall short in assessing non-weather water vulnerability.
• Key Risk Factors: Identify the main drivers of non-weather water damage.
• Strategic Insights: Discover strategies to improve your management of non-weather water claims.
• Z-WATER in Action: Experience our new AI-powered model that predicts non-weather water risk with unparalleled accuracy.
• Interactive Q&A: Get your questions answered by our experts.

Who Should Attend

This webinar is ideal for Executives, Product Managers, Actuaries, Underwriters, and CAT Modelers committed to enhancing their understanding and management of non-weather water risks. 

Bonus Content

As a bonus, you'll receive our exclusive infographic, "Below the Surface: Research Reveals Knowledge Gap in Homeowner Water Loss Prevention and Coverage."

This research gives key insights into water loss experiences, coverage details, homeowner protection measures, and information on water shutoff devices and heater conditions.

Register Now

It’s hard to overstate how important the roof is from an insurability standpoint. The roof represents significant risks and potential opportunities, making it a critical focus area for insurers. This has become even more important in recent years as the impact of severe convective storms is often reflected in roof losses. Understanding this, ZestyAI has released new research for property insurers called The Insurers Guide to Roof Risk.

Download The Insurers Guide to Roof Risk

In an era where the severity and frequency of roof-related claims are on the rise, particularly due to the increasing impact of severe convective storms, innovative tools and strategies are essential. The Insurers Guide to Roof Risk provides actionable insights to improve risk assessment, underwriting processes, and overall business strategy.

What’s Inside the Guide?

The Insurers Guide to Roof Risk includes:

• Roof Failure Factors: Learn the underlying contributing factors behind why older roofs fail more often.
• Beyond Roof Age: Discover why roof complexity, condition, and climate are more important than roof age alone.
• Identifying Missing Risk Factors: Understand the key factors to roof risk that most traditional models miss.
• Advanced Risk Segmentation: See how using machine learning and new data sources can split risk more than 60 times better than traditional models.
• Portfolio Optimization: Access a comprehensive toolbox to optimize your portfolio and new business selection to generate exponential lift versus traditional models.

Download Now

Annual Wildfire Season Overview provides insights to assist insurers in effectively managing wildfire risk.

ZestyAI has released its annual Wildfire Season Overview for 2024. This year’s guide provides critical insights carriers need to stay ahead of the rapidly evolving wildfire landscape. Offering more than just data, this year’s guide is designed to help insurers make informed risk decisions in some of the country’s most volatile states. 

Download ZestyAI's 2024 Wildfire Season Overview 

This year’s guide includes: 

• Countrywide Wildfire Impact Analysis: Understand how wildfires are affecting regions beyond traditional hotspots like CA, including significant events in TX & NM.
• Future Wildfire Trends: Explore predictions for the 2024 wildfire season and understand the long-term implications of current conditions on wildfire risks.
• Regulatory Insights: Stay updated on the latest regulations affecting wildfire risk assessment insurance practices.
• AI-driven Risk Models: Learn how ZestyAI's Z-FIRE model accurately predicts wildfire risks and assists insurers in making informed decisions.
• Property-Level Risk Assessments: Discover the importance of granular, property-specific risk evaluations to improve underwriting accuracy and transparency for consumers.

Download Now

Costing insurers approximately $19 billion every year, roof claims stand as the primary driver of property insurance losses.

Traditional methods of obtaining roof age information are deeply flawed. Most carriers depend on policyholder or agent-reported data, which is often inaccurate, leading to blind spots in assessing property risk. In a recent ZestyAI survey, 63 percent of homeowners reported not knowing the age of their roof if they were not in their homes the last time it was replaced.

Join our expert panel for a deep dive into leveraging roof age analytics for a cutting-edge underwriting process and gain insider knowledge on:

• The Leading Cause of Claims: unveil the hidden truths behind roof-related claims and the costly consequences of outdated assessment methods.
• A New Era of Data: Learn about ZestyAI’s pioneering approach to roof age analytics, incorporating building permits, historical imagery, and AI for a comprehensive view
• Precision at Scale: See how to apply precise, AI-driven roof age data across your entire portfolio for consistent and reliable underwriting and claims decisions
• Technical Decision Making: Empower your actuaries and underwriters with the insights needed to enhance risk selection and optimize pricing strategies
• Efficiency in Operations: Streamline inspections and operations, focusing resources where they’re needed most, improving time-to-quote, and enriching the customer experience
• Best Practices: Learn how leading carriers are using roof age, roof condition, and peril-specific models to improve risk selection and lower combined ratios 

This transformative session is available on demand. Learn how to enhance accuracy, efficiency, and profitability in property insurance.

Save Your Spot

In an ever-evolving regulatory environment, staying informed and adaptable is crucial. Our latest interactive guide, "When Innovation and Regulation Meet", offers a comprehensive toolkit for navigating the complexities of insurance compliance and the integration of AI technologies. 

What's Inside?

• Regulatory Landscape Map: Delve into a detailed state-by-state analysis, uncovering the intricacies of filing laws and approval speeds.
• Staying Ahead of Regulation Changes: Learn how to stay prepared and ensure your compliance strategies are future-proof, aligning with the latest regulatory expectations.
• Essential AI Partner Checklist: Choosing the right AI partner is crucial for success. Our guide offers a meticulous checklist for selecting a partner that is not only compliant but also transparent and supportive, ensuring you make an informed decision.
• Emerging Regulatory Concerns: What do you need to know about privacy, bias, and AI oversight?
• Real-World Applications: Discover how ZestyAI's collaborative approach with regulatory entities has led to successful model approvals across the United States. 

Why This Guide?

As the regulatory framework becomes increasingly complex, having a reliable and insightful resource is indispensable. Our guide is tailored for insurance professionals seeking to enhance their regulatory strategy, embrace AI innovation responsibly, and achieve a competitive edge in the market.

Ready to get up to speed on 2024's regulatory environment? Access the guide.

The landscape of hail risk management is undergoing a significant transformation. Our latest publication, "Hail Risk 2024: An Interactive Guide for Insurers," offers a critical examination, illustrated with compelling data, of the factors contributing to the alarming rise in hail-related losses over the last decade. Major changes to how hail is understood have changed how insurers should view the peril. This guide isn't just about understanding hail risk; it's about redefining how it is managed in the insurance industry.

Why This Guide is Indispensable:

• Losses Rising — Understand the key factors driving record-breaking hail losses, and why there's more to the story than just "climate change."
• Reinsurance  — Learn why insurance carriers now shoulder more of the burden due to changing risk transfer relations.
• The Right Tools  — Explore how AI-based climate risk models are supplementing stochastic and actuarial models for a full picture of climate risk.
• Actionable Steps  — See how leading carriers are applying granular, property-level insights and learn the proactive steps they're taking to mitigate risks and losses.

Ready to get up to speed on hail risk in 2024? Access the guide.

New research from ZestyAI reveals that 62% of U.S. homeowners are deferring critical home maintenance, adding up to $317 billion in potential claims exposure for insurers.

These findings come as Severe Convective Storms (SCS) caused an estimated $58 billion in insured losses in 2024, surpassing hurricane-related losses and marking the second-costliest SCS year on record.

Tornadoes, hail, and wind events now account for over 60% of all U.S. catastrophe claims, and research from the Insurance Institute for Business & Home Safety (IBHS) shows that roof damage accounts for up to 90% of residential catastrophe losses.

Key Findings from ZestyAI’s Homeowner Survey

According to ZestyAI’s nationally representative survey, 62% of homeowners have delayed essential repairs due to budget constraints, representing nearly 59 million U.S. homes with unaddressed vulnerabilities. Forty percent said they would rely on an insurance claim to cover major repairs like roof replacement, adding up to an estimated $317 billion in potential exposure for carriers.

Alarmingly, 63% of homeowners who weren’t living in their home at the time of the last roof replacement don’t know how old their roof is, making it even harder to detect aging systems before they fail. Meanwhile, 12% admitted they would delay repairs indefinitely, further increasing their risk of property damage.

Severe Convective Storms: The Growing Catastrophe Risk

This blind spot compounds known risks: prior ZestyAI analysis has identified over 12.6 million U.S. properties at high risk for hail-related roof damage, representing $189.5 billion in potential roof replacement costs.

“Deferred maintenance has long been a known risk factor, but today the stakes are higher than ever,” said Kumar Dhuvur, Co-Founder and Chief Product Officer of ZestyAI. "With claim severity rising and storm losses compounding, insurers need more than hazard maps to navigate this landscape."

"Property-level insights allow carriers to proactively address known vulnerabilities, improve underwriting precision, and work with homeowners to reduce losses before they happen.”

ZestyAI’s findings support a growing push toward data-driven, preventative underwriting strategies, especially as carriers face rising claim severity and pressure to improve combined ratios across storm-prone states.

In today’s property insurance market, understanding wildfire risk at the individual structure level is more critical than ever. For wholesale brokers like Jencap, the ability to deliver actionable, data-driven insights to retail agents and carriers is essential, especially as wildfire conditions evolve rapidly across the country.

That’s why JenCap turned to ZestyAI.

In the video above, Ben Beazley, EVP and Head of Property at JenCap, shares two key reasons why ZestyAI’s Z-FIRE™ model stood out:

• Structure-level precision: Z-FIRE analyzes wildfire risk at the individual property level—factoring in building materials, defensible space, vegetation, topography, and historical fire patterns to predict which homes are most vulnerable and which are more likely to withstand a fire.
• Continuously refreshed data: While the core model remains stable and DOI-approved, Z-FIRE is updated with the latest fire perimeters, confirmed loss locations, and vegetation data. This ensures it reflects the most current wildfire seasons and emerging risk patterns.
• Z-FIRE is already approved for rating and underwriting in every major wildfire-prone state. For JenCap and many others, it’s become a vital tool for evaluating wildfire exposure and supporting smarter decisions in high-risk areas.

Not every wildfire spreads through forests. Some move house to house, block to block, driven by wind, heat, and proximity. As these events become more common, insurers are asking sharper questions about how to assess risk in densely built environments.

Z-FIRE was designed to account for the real-world conditions that enable this type of fire behavior, capturing the structural, spatial, and environmental factors like building density, defensible space, mitigation strategy, climatology, and slope that contribute to urban conflagration.

What Is Urban Conflagration?

Urban conflagration refers to a fire that spreads rapidly through a densely built environment, jumping from structure to structure rather than moving solely through vegetation. Unlike traditional wildfires that primarily burn forests or grasslands, these events are driven by building materials and the adoption of fire mitigation practices, the spacing between structures, and proximity to areas that are known to be challenging for firefighters.

Wind and terrain—particularly steep slopes—often accelerate the spread, pushing fire fronts into residential areas and compounding the risk of widespread destruction. For insurers, urban conflagrations represent a uniquely challenging peril, where fire behavior is shaped as much by the built environment as by natural fuels. Without a model built to capture these dynamics, they’re nearly impossible to assess accurately.

We’ve seen what happens when wind-driven embers reach tightly packed communities. In fires like Marshall, Lahaina, and the recent Palisades and Eaton Fires, wildfires didn’t stop at the wildland-urban interface—they became full-scale urban conflagrations.

These events are stark reminders that wildfire risk doesn’t end at the edge of the forest and that densely populated areas can produce concentrated, catastrophic losses.

For insurers, these events raise a critical question: Where are the next high-concentration loss scenarios hiding in the portfolio?

When urban conflagration strikes, damage rates spike, and PML exposure can increase exponentially. Identifying the neighborhoods where construction patterns, terrain, and fuel conditions create the potential for that kind of fire behavior is no longer optional; it’s essential. 

At ZestyAI, we’ve been asking, and answering, these questions for years. The Z-FIRE model was designed to do exactly that.

Built to Reflect Real-World Urban Risk

From its inception,  Z-FIRE has accounted for the drivers of urban conflagration. Its two-level architecture combines neighborhood-level dynamics with property-specific characteristics, offering a detailed and scalable view of wildfire risk—even in densely built environments.

Level 1 (L1): Neighborhood Risk Score

L1 predicts the likelihood that a property will fall within a wildfire perimeter. It does this by analyzing climatology, historical wildfire behavior, terrain, fuel type, and wildfire suppression ratings to understand where fires are likely to start, spread, and grow.

Two variables are particularly important for identifying urban conflagration risk:

• Fuel Type, which accounts for both vegetative fuels and the built environment. In densely developed areas, clusters of structures can serve as fuel, particularly when combined with slope, dry conditions, or limited defensible space.
• Wildfire Suppression Rating (WSR), which indicates areas where fire suppression is likely to fail due to access, water availability, or firefighting capacity. Rather than relying on WSR alone, Z-FIRE factors in proximity to high and very high WSR zones, enabling it to capture risk spillover into nearby neighborhoods.

What sets Z-FIRE apart is how these variables interact. The model doesn’t assess them in isolation—it evaluates how multiple risk factors compound one another. This layered, interaction-driven approach allows Z-FIRE to surface hidden vulnerabilities that simpler, one-dimensional models often miss and accurately identify regions with high conflagration risk.

• L1 evaluates wildfire risk based on local terrain, fuel types, and building density. Critically, Z-FIRE incorporates two critical variables that are key indicators of conflagration risk. Both “fuel type” and proximity to areas with a High or Very High wildfire suppression rating.
  • Fuel Type accounts for both vegetation and for developed land characteristics. While vegetative fuel and its management are key for wildfire, building density can become a large contributor to conflagration risk if combined with the other high-risk factors. It is important to remember that Z-FIRE allows for unlimited variable interaction; a high-density neighborhood can be at high risk of other factors, contributing to conflagration risk.
  • Wildfire Suppression Rating (WSR) reflects the risk that a high-intensity fire may become impossible to manage by firefighters. Because those areas tend to be located in the WUI, Z-FIRE does not only rely on the WSR score, but also uses the distance proximity to high or very high WSR.

Level 2 (L2): Property-Specific Risk Score

At the structure level, L2 evaluates both nearby vegetation and building fuel density, a key driver of structure-to-structure ignition. This metric, validated by the Insurance Institute for Business & Home Safety (IBHS), helps Z-FIRE model how a single ignition can escalate within tightly packed neighborhoods, even in the absence of natural fuels.

Z-FIRE was trained on real-world events with clear urban conflagration patterns. In the 2017 Tubbs Fire, for example, flames spread deep into Santa Rosa, destroying dense subdivisions like Coffee Park. Similarly, recent fires such as Palisades and Eaton moved rapidly through built-up areas, where tightly spaced structures provided a continuous path of fuel.

Case in Point: Palisades and Eaton, CA

In the recent Palisades and Eaton Fires, Z-FIRE’s predictive accuracy was once again put to the test. Our analysis showed that over 91% of the affected area was already classified by Z-FIRE as high or very high risk based on Level 1 (L1) neighborhood scores.

Notably, none of the impacted areas were categorized as “Very Low Risk,” a strong validation that Z-FIRE captured the inherent vulnerability of these communities well before ignition.

Looking at Level 2 (L2) property-specific scores, the correlation between predicted risk and actual destruction became even clearer.

Structures with the highest Z-FIRE risk scores were 50% more likely to be destroyed compared to those with the lowest scores in the same fire footprint.

These destruction rates align with the model’s fundamental architecture: properties with denser surrounding structures, minimal defensible space, and combustible fuels nearby face a dramatically higher likelihood of loss during a wildfire.

The model identified risk in this community not simply based on topography or vegetation, but because of its underlying urban structure, including building materials, spacing between homes, and neighborhood density. These are the very factors that drive vulnerability to conflagration.

Z-FIRE was designed to capture these dynamics, reinforcing its value as a forward-looking tool for rating, underwriting, and mitigation planning.

A Model Informed by What’s Happening on the Ground

Wildfire conditions are constantly changing, and Z-FIRE stays current by continuously incorporating the latest ground-truth data, including updated fire perimeters, confirmed loss locations, and vegetation conditions.

While the core model remains stable and fully approved for rating and underwriting, this steady stream of fresh data ensures that Z-FIRE reflects the most recent fire seasons and emerging risk patterns.

The 2023 and 2024 fire seasons reinforced what we’ve long understood: fire behavior is increasingly shaped by the built environment. Z-FIRE continues to perform as expected across a wide range of scenarios, including structure-to-structure ignition in densely built areas.

These results reaffirm the model’s ability to provide timely, reliable insights to support carrier decision-making in a rapidly evolving risk landscape.

Available Now, for Those Who Need It Most

For carriers looking to better understand and underwrite wildfire risk, whether in traditional WUI zones or increasingly vulnerable urban neighborhoods, Z-FIRE offers a tested, approved, and field-proven solution.

‍Built on over a decade of confirmed loss data and designed to capture the drivers of urban conflagration, Z-FIRE supports smarter decisions across pricing, underwriting, mitigation, and reinsurance.

Importantly, Z-FIRE is approved for underwriting and rating by Departments of Insurance (DOIs) across all western states, with Oklahoma recently added to the list. Carriers can deploy the model today with confidence, knowing it meets regulatory standards while delivering granular, property-specific insights to support risk selection, pricing, and mitigation strategies.

If you're looking to validate wildfire risk insights on your own book of business, we invite you to put Z-FIRE to the test. Our team can run a targeted evaluation to show how the model performs across your portfolio, highlighting risk segmentation opportunities and identifying properties most vulnerable to structure-to-structure spread.

Get in touch to schedule an evaluation and see how Z-FIRE can strengthen your wildfire strategy today.

ZestyAI today announced the launch of ZORRO Discover™, a generative AI agent that delivers instant insights into regulatory filings and competitive market activity.

Solving a $2.5 Billion Regulatory Research Problem

Regulatory research remains one of the costliest inefficiencies in insurance, with an estimated $2.5 billion spent annually on manual reviews. The process consumes millions of hours across fragmented workflows, as filings often stretch into the thousands of pages, slowing competitive analysis and strategic decision-making.

To solve this, ZestyAI built ZORRO Discover on a proprietary generative AI pipeline, leveraging large language models optimized for insurance-specific content, including filings, objections, responses, and regulations from all 50 states.

Using agentic AI, the platform proactively navigates and synthesizes regulatory data, delivering a fast, intuitive experience tailored to the structure and language of insurance filings.

Accelerating Research by 95%

Early adopters of ZORRO Discover have found that insurers can cut research time by an average of 95%, saving thousands of work hours and millions in costs.  

“For too long, regulatory filings have buried critical intelligence under layers of complexity,” said Kumar Dhuvur, Founder and Chief Product Officer of ZestyAI. “Through years of working closely with regulators, we’ve come to deeply understand these challenges.”

“ZORRO Discover puts that intelligence at insurers’ fingertips so they can act faster, stay compliant, and make smarter decisions in an increasingly competitive market.”

How Teams Use ZORRO Discover

ZORRO Discover can be used by compliance, actuarial, product, and strategy teams to accelerate competitive research and reduce regulatory risk. By replacing manual reviews with a consistent, repeatable process, the platform helps teams improve research accuracy, focus on high-impact work, and stay ahead of regulatory changes.

Key Capabilities

• Plain-language search: Analyze and compare filings across carriers, states, and time periods using intuitive queries—no deep regulatory or technical expertise required.
• Zero in on critical details instantly: Transform complex filings into executive-level insights for faster, more informed decision-making.
• Spot market opportunities early: Track shifts in rates, rules, forms, and guidelines to anticipate industry trends and act proactively.
• Run side-by-side comparisons: Evaluate pricing strategies, regulatory objections, or model usage over time and across competitors. Example: Compare windstorm mitigation discounts across three major carriers in Florida.

Expanding to Additional Lines of Business

ZORRO Discover launches with a focus on homeowners insurance and is rapidly expanding to support regulatory and competitive intelligence across auto, commercial, and additional lines of business.

Request early access to ZORRO Discover here.

The Arizona Department of Insurance and Financial Institutions has approved the use of ZestyAI’s Severe Convective Storm suite, including Z-HAIL™, Z-WIND™, and Z-STORM™, giving insurers access to property-level risk insights.

Rising Storm Losses Across Arizona

In Arizona, the most frequent and damaging thunderstorm losses stem from strong, straight-line winds, especially downbursts. These sudden, localized wind events can exceed 100 mph and often cause significant roof and structural damage, particularly in vulnerable homes.

In 2024 alone, Arizona experienced 67 days of severe storm events, according to NOAA. These included high winds, large hail, tornadoes, and damaging downbursts, highlighting the growing volatility of the state’s monsoon season and the increasing threat to both rural and urban communities.

How ZestyAI’s Models Improve Precision

ZestyAI’s models are designed to address these risks. By analyzing how local climatology interacts with individual property features, the platform predicts both the likelihood and severity of storm-related claims, offering a more accurate alternative to traditional ZIP code or territory-based approaches, which often miss critical risk signals.

Each model is trained and validated on extensive real-world claims data and provides clear, transparent explanations of the key factors driving each score, enabling more confident underwriting and rating decisions.

Key Model Capabilities

• Z-HAIL: Predicts hail damage risk and claim severity using property-specific attributes like roof complexity, historical losses, and accumulated damage, identifying which homes are most likely to file a claim, even within the same neighborhood.
• Z-WIND: Combines AI-generated 3D analysis of roof condition, complexity, and potential failure points with local climatology to deliver pivotal insights into property-specific wind claim vulnerability and severity.
• Z-STORM: Predicts the frequency and severity of storm damage claims, including hail and wind, examining the interaction between climatology and the unique characteristics of every structure and roof.

Regulatory Confidence in AI-Driven Models

Bryan Rehor, Director of Regulatory Affairs at ZestyAI said,

“Arizona is a key market for many of our carrier partners, and one of the most rigorous regulatory environments for model review. This approval is a strong signal of confidence in our technology and our commitment to transparency, precision, and regulatory alignment.”

Arizona marks the 19th state to approve ZestyAI’s Severe Convective Storm suite—and the fourth model approved in Arizona overall, joining Z-FIRE™, ZestyAI’s AI-powered wildfire risk model already in use across the state. With elevated risk across multiple perils, Arizona’s adoption of ZestyAI’s models reflects growing regulatory confidence in AI-driven models that enable smarter underwriting, precise pricing, and stronger resilience in the face of extreme weather.

At our 2025 offsite, we had the rare privilege of hosting Scott Stephenson, former Chairman, President, and CEO of Verisk, for a candid fireside chat with our CEO, Attila Toth.

More than a guest speaker, Scott has been a mentor to our founders and a steady source of insight and encouragement on our journey. 

Over two decades, he led Verisk through extraordinary growth: doubling revenue, quadrupling market cap, and shaping one of the most respected analytics companies in the world. Named one of Forbes’ Most Admired CEOs, Scott helped define the modern insurance ecosystem.

But what stayed with our team long after the session wasn’t the accolades. It was his clarity, humility, and deep conviction that great companies aren’t defined by vision—they’re defined by execution.

Here are three takeaways that stuck with us:

Trust is a survival skill

Scott opened with the story of the 1949 Mann Gulch wildfire, where only 3 of 16 elite smokejumpers made it out alive. The team leader lit an escape fire and lay down inside it. He shouted for the others to follow, but no one did.

“They were a team on paper,” Scott said, “but they’d never trained together. They didn’t trust each other enough to act as one.”

The lesson? In high-stakes environments, technical talent means little without trust. Success depends on how quickly and cohesively a team can move together.

Thinking isn’t doing

Smart teams often confuse planning with progress. As Scott put it:

“Thinking about something, even deeply—and talking about it with others—feels like you’re doing the work. But you’re not.”

Insight without execution is just potential energy. The companies that thrive aren’t the ones with the most ideas; they’re the ones that ship, iterate, and improve with discipline.

Leadership is a mindset

Scott began his career as an engineer. Leadership wasn’t on his radar—until curiosity led him to explore it. His message: leadership isn’t a job title, and it’s not reserved for MBAs. It belongs to those who take responsibility, act with principle, and stay grounded in reality.

Why it mattered

Scott didn’t come to ZestyAI to celebrate the past. He came to challenge us. To remind us that in an industry facing rising losses, regulatory pressure, and rapid change, progress isn’t driven by buzzwords or strategy decks. It’s driven by clarity, trust, and the discipline to do the hard work.

That message hit home. As we scale ZestyAI, our ambition isn’t just to innovate; it’s to lead with purpose. To build the new standard for risk analytics. One that helps insurers price with precision, expand access to coverage, and strengthen the resilience of entire communities.