Reports & Research

The Silent Peril Reshaping Homeowners Insurance

Non-weather water damage rarely makes headlines, but it’s quietly eroding profitability across the country.
It is now the fourth costliest peril in homeowners insurance, and claim severity has increased 80% in the last decade—a trend that’s accelerating even as frequency remains relatively flat.

Traditional risk models struggle to capture the early warning signs behind these losses, leading to mispriced policies, undetected exposure, and rising volatility for carriers.

Want the full analysis? Download the complete “Winning the Fight Against Non-Weather Water Losses” guide.

Why Loss Severity Keeps Rising

Aging homes and overlooked system failures

Many of the most expensive losses stem from aging plumbing, deteriorating materials, and slow-burn failures that often go undetected until damage is significant.

Frequency is flat—severity is not

Loss patterns suggest that while the number of events hasn’t surged, the financial impact of each event has—a signal that traditional models are not capturing the right property-level predictors.

The Property Features Most Predictive of Water Losses

The overlooked attributes that traditional models miss

Standard territory- or age-based assessments often ignore the property-specific details that meaningfully influence water loss risk, including:

• supply line material and age
• plumbing configuration
• occupancy patterns
• system maintenance and upgrades
• moisture exposure and prior loss indicators

These factors vary widely between neighboring homes—yet most models treat them as identical.

Where Traditional Underwriting Falls Short

ZIP-code and age-based proxies mask true risk

Legacy approaches rely heavily on broad territory-level assumptions that overlook structural vulnerabilities and system conditions.

Limited visibility creates mispriced policies

Without property-level insight, high-risk homes are often underpriced while lower-risk homes subsidize them—driving loss ratio volatility over time.

Get deeper insights on the drivers of water loss severity in our full guide → “Winning the Fight Against Non-Weather Water Losses”

How AI and Property-Level Data Are Changing the Landscape

AI models trained on real-world claims data can identify early signals of potential water loss by analyzing the interaction between:

• plumbing systems
• property attributes
• historical patterns
• material degradation
• repair history

This enables carriers to segment risk accurately, adjust pricing, and reduce preventable losses—long before small issues turn into major claims.

What Homeowners Actually Understand About Water Risk

Misconceptions around coverage and prevention

ZestyAI’s research shows that many policyholders:

• misunderstand what is and isn’t covered
• underestimate how much damage water can cause
• rarely take preventive actions unless prompted

This disconnect creates an opportunity for carriers to strengthen education, mitigation, and customer engagement.

Steps Carriers Can Take Today

Improve segmentation and rating accuracy

Property-level signals enable more precise risk tiers and more stable long-term portfolios.

Strengthen mitigation and reduce loss severity

Insights help identify which homes are at elevated risk and where targeted mitigation can reduce exposure.

Enhance underwriting workflows with explainable insights

Transparent, explainable AI helps underwriters understand the key drivers behind elevated risk—supporting both decision-making and regulatory review.

Get the Full Guide

Our new research paper, Winning the Fight Against Non-Weather Water Losses, breaks down the trends reshaping this growing peril—and the strategies carriers can use to get ahead of it.

Access the Guide

ZestyAI's analysis revealed that more than 12.6 million U.S. properties are at high risk of hail-related roof damage, representing $189.5 billion in potential replacement costs.

Powered by ZestyAI’s Z-HAIL™ model, the analysis underscores the growing financial threat of severe convective storms (SCS), including hail, tornadoes, and wind events. In 2024 alone, damages from SCS were estimated at $56 billion—surpassing losses from hurricanes.

Yet many insurers still rely on traditional models designed to estimate portfolio-level exposure, not property-level risk. As hail events increase in severity and frequency, these models often miss the structural and environmental conditions that drive real losses.

Kumar Dhuvur, Co-Founder and Chief Product Officer at ZestyAI said:

“Catastrophe models have helped insurers understand where storms may strike and how losses might add up at a portfolio level. But they weren’t built to assess risk at the individual property level, and they often miss the specific conditions that drive hail damage. By analyzing the interaction between structure-specific features and local storm patterns, we can distinguish risk between neighboring properties—enabling smarter underwriting, more precise pricing, and better protection for policyholders.”

Z-HAIL evaluates hail risk using a proprietary blend of climate, aerial, and property-specific data. By applying advanced machine learning to these inputs, Z-HAIL delivers highly granular predictions that reflect both the physical characteristics of a structure and the storm activity in its immediate surroundings.

Key findings from the analysis:

• 12.6 million U.S. structures flagged as high risk for hail-related roof damage
• $189.5 billion in total potential roof replacement exposure

Top five states by dollar exposure:

• Texas ($68B)
• Colorado ($16.7B)
• Illinois ($10.8B)
• North Carolina ($10.4B)
• Missouri ($9.5B)

States with the lowest dollar exposure:

• Maine ($4.7M)
• Idaho ($12.8M)
• New Hampshire ($18.5M)
• Nevada ($49.3M)
• Vermont ($64.7M)

In recent case studies, Z-HAIL has demonstrated the ability to pinpoint which properties are most susceptible to hail damage—even within the same neighborhood and exposed to the same storm. In one example from Allen, Texas, following a storm with 2.5-inch hailstones, Z-HAIL segmented risk across 483 policies, identifying no losses among properties rated “Very Low” by the model. This level of intra-territory precision gives insurers the ability to refine risk selection with confidence—even in the most hail-prone regions of the country.

Severe convective storms are becoming more frequent and costly, putting pressure on insurers to refine underwriting and risk management strategies. 

On April 2, our experts covered:

• Key drivers behind increasing severe storm losses
• What La Niña means for the 2025 season
• How AI-powered risk models improve risk segmentation
• Live Q&A – Get expert answers to your toughest questions!

Missed the live event? Stream now! 

Severe convective storms (SCS)—including tornadoes, hail, and damaging wind events—resulted in $58 billion in insured losses across the U.S in 2024.

Insurers face a dual challenge: navigating the uncertainty of storm patterns while ensuring their portfolios remain resilient enough to absorb the financial strain from clustered, high-loss events.

Research with IBHS confirms that SCS damage accumulates over time, particularly affecting rooftops after multiple exposures to intense storm activity. As housing stock deteriorates, insurers must reassess their portfolios to ensure underwriting, rating, and loss cost controls align with their risk appetite and maintain premiums that accurately reflect evolving exposure.

Get ahead of rising storm risks with expert insights that help you strengthen underwriting, risk assessment, and claims management.

Get our new report.

A staggering $2.15 trillion worth of U.S. residential property is at high risk of wildfire damage, according to a new AI-powered analysis from ZestyAI, the leader in climate and property risk analytics. The study, which assessed 126 million properties nationwide, found that 4.3 million individual homes face heightened wildfire risk—far beyond traditionally recognized high-risk areas.

Using advanced AI models trained on over 2,000 historical wildfires, ZestyAI mapped wildfire exposure at the property level, integrating satellite and aerial imagery, topography, and structure-specific characteristics. While California leads the nation with $1.16 trillion in wildfire-exposed property, other states such as Colorado ($190.5 billion), Utah ($100.3 billion), and North Carolina ($71.2 billion) also face significant risk.

Wildfire Risk is a Nationwide Challenge

While the Western U.S. has historically seen the most severe wildfire activity, ZestyAI’s findings confirm that high-risk properties exist across the country. States like North Carolina (4.6% of homes at high risk), Kentucky (2.9%), Tennessee (2.3%), and even South Dakota (11.0%) are now seeing increased wildfire exposure.

As more homes and businesses are built in fire-prone landscapes, the Wildland-Urban Interface (WUI) continues to expand. This, combined with intensifying climate conditions, is driving higher insurance costs and growing availability concerns. Today, one in eight U.S. homeowners already lacks adequate insurance coverage, and that number is expected to rise.

AI Expands Insurance Access in High-Risk Areas

Attila Toth, Founder and CEO of ZestyAI said:

"Wildfires are threatening more properties than ever before, with billions of dollars in exposure even in areas many people don’t associate with fire risk. Yet, too many homeowners are finding themselves uninsured or underinsured just as these disasters become more frequent and severe. Insurers have traditionally relied on broad, regional models that don’t account for individual property characteristics."

"That means some homeowners are denied coverage even when their true risk is much lower than their neighbors'.’"

AI-driven risk analytics are reshaping the way insurers assess wildfire exposure. By providing granular, property-specific insights, we’re helping insurers make smarter underwriting decisions—keeping coverage available in high-risk areas while ensuring that homeowners who take mitigation steps are recognized.

Last year, our models helped insurers extend coverage to 511,000 properties that had previously struggled to secure insurance due to outdated risk models. In 2025, we expect that number to reach a million, ensuring that even in high-risk areas, responsible homeowners have access to protection when disaster strikes.

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.

ZestyAI, the leading provider of AI-driven risk analytics for the property and casualty insurance industry, today announced it has secured a $15 million credit facility from CIBC Innovation Banking.

The facility enhances ZestyAI’s financial flexibility and reinforces its strong balance sheet as the company scales adoption of its climate and property risk models, delivering over 31 million property risk assessments in 2024, more than double the volume from 2023, and on pace to exceed 50 million in 2025.

“We’ve built ZestyAI with long-term discipline and a clear mission: to help insurers navigate changing risks with confidence,” said Attila Toth, Founder and CEO of ZestyAI.

“As demand for trusted, property-level risk insights continues to grow, this capital infusion enables ZestyAI to further invest in supporting this rapid growth and become the industry standard for property risk analytics."

Strengthening ZestyAI’s Position for Rapid Growth

Capital that supports scale, product expansion, and customer demand

“ZestyAI is addressing a critical need in the insurance industry with its AI-powered approach to property and climate risk,” said Sean Thompson, Managing Director, California Market Manager at CIBC Innovation Banking.

“We’re proud to support ZestyAI’s next phase of growth as it continues expanding its platform and deepening its impact across the insurance ecosystem.”

ZestyAI’s footprint has expanded rapidly across the insurance landscape, with growing adoption among admitted carriers, MGAs, the E&S market, FAIR Plans, and public-private partnerships. Over the past year, the company secured 33 new and expanded customer partnerships, including 26 brand-new clients, and launched four new products.

Accelerating Regulatory Momentum Nationwide

This growth has been matched by accelerating regulatory traction. ZestyAI’s AI-driven models for wildfire, severe convective storms, and non-weather water damage have now been approved in over 50 regulatory filings nationwide, with recent approvals in Texas, Colorado, Ohio, Georgia, Connecticut, Michigan, North Carolina, Louisiana, and Oklahoma.

Recently reviewed by the California Department of Insurance (CDI) in the rate application process, Z-FIRE™, ZestyAI’s wildfire model, can continue to be filed for rate segmentation and underwriting without further review under the Pre-Application Required Information Determination (PRID) process, effective January 2, 2025.

Fueling a Mission to Expand Access to Coverage

Built at the intersection of property data, climate science, and AI, ZestyAI’s platform delivers precise, parcel-level risk insights that help insurers strengthen underwriting, price accurately, optimize inspections, and expand coverage, especially in catastrophe-prone regions. In 2024, ZestyAI helped carriers and insurers of last resort extend coverage to over 511,000 properties previously deemed uninsurable, advancing its mission to protect the livelihoods of homeowners, business owners, and their communities.

As Colorado’s HB 1182 introduces new requirements for wildfire risk transparency and mitigation recognition, ZestyAI is helping insurers comply with proven, mitigation-ready solutions.

What HB 1182 Requires from Insurers

Recently signed into law, HB 1182 requires insurers to disclose how wildfire risk models impact rates, account for property- and community-level mitigation efforts, notify policyholders annually of their risk scores and available discounts, and provide a clear appeals process for disputed scores.

The new regulations take effect July 1, 2026, across homeowners and condo policies, including admitted carriers and the FAIR Plan.

Carriers need to move early to ensure their risk models, rating plans, and customer communications meet the law’s requirements. ZestyAI’s explainable AI models are already in use by the Colorado FAIR Plan and leading carriers to assess mitigation and support policyholder communications in Colorado and other wildfire-prone states.

"As regulatory expectations around transparency and customer engagement continue to evolve, HB 1182 sets a clear framework for wildfire risk modeling," said Bryan Rehor, Head of Regulatory Affairs at ZestyAI.

"ZestyAI’s models were built with these principles in mind, offering carriers a proven, low-friction way to meet these requirements while delivering a better experience to policyholders."

How ZestyAI Helps Carriers Meet HB 1182 Requirements

• Built for Transparency: ZestyAI’s explainable AI models allow carriers to clearly communicate how risk scores are generated, what factors are considered, and how mitigation actions influence risk.
• Mitigation-Ready Risk Modeling: Property- and community-level mitigation efforts are integrated into risk assessments, supporting discounts and appropriate pricing.
• Consumer Risk Score Disclosures: ZestyAI enables carriers to generate individual risk scores and mitigation factors for annual policyholder notifications.
• Appeals and Score Adjustments: Carriers can update risk scores in real time based on new property information, offering transparency and responsiveness to policyholders.
• Regulatory Alignment: ZestyAI’s wildfire, hail, wind, and severe storm models have been reviewed and approved for use in Colorado, helping carriers meet standards with confidence.
• Multi-State Scalability: Carriers can streamline compliance across Colorado and other regulatory environments using the same ZestyAI platform.

A Clear Path to Compliance in Colorado—and Beyond

ZestyAI maintains strong relationships with state insurance regulators and actively participates in dialogue around evolving requirements.

At the national level, ZestyAI engages with organizations such as the NAIC and leading industry advocacy groups to stay ahead of broader regulatory trends.

Through in-house Rating and Advisory organizations, ZestyAI files its models directly with state departments of insurance, ensuring each solution is rigorously vetted and aligned with jurisdiction-specific standards before reaching the market.

ZestyAI today announced a four-year expansion of its partnership with the California FAIR Plan.

Since 2021, the insurer of last resort has leveraged ZestyAI’s Z-FIRE™ to enhance risk assessment, ensuring that homeowners unable to obtain private insurance still have access to wildfire coverage.

How Z-FIRE Supports Access to Wildfire Coverage

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

The model leverages AI-driven analysis of over 2,000 historical wildfires, integrating satellite and aerial imagery, topography, and property-level characteristics to provide precise, property-specific risk assessments.

‍This scientifically validated approach is backed by decades of research, including studies from the Insurance Institute for Business & Home Safety (IBHS).

“We’re honored to continue supporting the California FAIR Plan in providing reliable insurance coverage in high-risk regions,” said Attila Toth, Founder & CEO of ZestyAI.

“By providing Z-FIRE scores directly to policyholders, the California FAIR Plan has increased transparency around wildfire risk and empowered homeowners to take meaningful mitigation steps—like defensible space measures and fire-resistant building materials—to better protect their homes and communities.”

ZestyAI works closely with regulators to ensure transparency, validation, and continuous monitoring of its AI-driven models.

Regulatory Alignment Across the Western U.S.

The company has secured key regulatory approvals across the U.S., including all Western states for Z-FIRE and broad acceptance of its severe convective storm models from Texas to Colorado, the Midwest, and the Great Plains.

The California Department of Insurance (CDI) has reviewed Z-FIRE as part of recently approved rate filings. Insurers can continue filing to use the model for rate segmentation and underwriting without additional review under the Pre-Application Required Information Determination (PRID) process.

Building on its success in California, ZestyAI has partnered with other insurers of last resort, including the Colorado FAIR Plan, further expanding the adoption of AI-driven risk models to help protect families and communities.

Insurance carriers have long relied on aerial imagery to assess property risk, but not all imagery offers the same level of insight. Oblique imagery—angled aerial photos that show the sides of buildings, not just the rooftops—is gaining traction as an essential tool for property underwriting, inspections, and claims.

ZestyAI is proud to now offer oblique imagery from major imagery providers directly within our platform. That means carriers get access to the most comprehensive, up-to-date, and high-resolution views available, streamlined into a single interface, and always in context with our industry-leading property risk insights.

Why Oblique Imagery Matters

Unlike traditional top-down (orthogonal) imagery, oblique views provide side-angle perspectives that reveal critical features often missed from above. This added dimension helps insurers:

• Spot more risk factors: Identify decks, porches, attached structures, handrails, and overhangs—details that are often invisible from above but meaningful for underwriting and rating.
• Gain a more complete picture: Assess roof geometry and slope, siding condition, and visible maintenance issues without needing an in-person inspection.
• Underwrite with confidence: Reduce uncertainty in borderline or complex risks by giving underwriters a full visual context.
• Support faster claims verification: Pre-loss oblique imagery strengthens documentation, helps reduce disputes, and expedites claim handling.

As Rick Smith, Underwriting Manager at Standard Casualty, explains:

“We can get overhead and oblique shots of those locations. We can accomplish through aerial photography what we do through an on-site inspection at a fraction of the cost, which is really important for us.”

The Problem: Fragmented, Outdated, or Incomplete Views

Many carriers still rely on patchwork imagery or public sources like Google Street View.

The result?

• Coverage gaps: Rural, coastal, or wildfire-prone regions may not be frequently or adequately captured, leaving insurers with limited visibility in high-risk areas.
• Stale or seasonal views: Images can be several years old or captured in winter conditions, where snow, shadows, or vegetation obscure key features. Public tools like Google Street View are often even more outdated, sometimes by five years or more.
• No risk context: Raw imagery alone doesn't tell the full story. Without integrated risk scores or property intelligence, it’s just a picture, not a decision-making tool. 

These challenges lead to slower decisions, higher inspection costs, and greater exposure to unknown risks.

ZestyAI’s Advantage: A Complete, Unified View

ZestyAI removes these roadblocks by offering a seamless, integrated oblique imagery experience, built directly into our property risk platform. Here’s what sets us apart:

• Aggregated imagery from major providers: No more relying on a single source. We deliver the widest available footprint and intelligently surface the best imagery for each property.
• Highest recency and resolution: Our platform automatically displays the most recent, clearest, and most relevant imagery available, so you never miss what matters.
• Contextualized insights: Oblique views are shown alongside our AI-powered risk scores and property features, empowering faster and more informed decisions.
• Workflow-ready: Designed for use across underwriting, inspection triage, and claims support, with full scalability for enterprise teams.

Real Impact for Carriers

Insurers using ZestyAI’s oblique imagery capabilities are already seeing measurable improvements:

• Reduced reliance on field inspections
• More accurate roof and structure classifications
• Faster quote turnaround with fewer touchpoints
• Better risk segmentation and fewer surprises at renewal

Combined with ZestyAI’s property-level risk models for perils like wildfire, severe storms, and water damage, oblique imagery helps carriers make decisions with more confidence and clarity every step of the way.

See What You’ve Been Missing 

Oblique imagery adds a critical dimension to property assessment, and when it’s seamlessly integrated with ZestyAI’s AI-powered insights, the result is faster decisions, better risk selection, and more confident underwriting.

See your risk from every angle. 

Schedule a demo today.

ZestyAI today announced a new partnership with Kin Insurance, a direct-to-consumer, digital home insurance provider committed to serving catastrophe-exposed markets.

As part of its expansion into California, Kin has deployed Z-FIRE, ZestyAI’s wildfire risk model, to accurately assess property-level wildfire exposure and expand access to coverage in high-risk areas.

The model was integrated in just 10 days, enabling Kin to move quickly in meeting the needs of California’s evolving market.

Meeting California’s Growing Need for Property-Level Wildfire Insight

California continues to face a widening insurance gap, driven by more frequent natural disasters and insurer withdrawals.

This partnership supports Kin’s commitment to bringing insurance options back to communities impacted by limited availability of coverage.

Z-FIRE uses machine learning to evaluate each property’s unique characteristics, including defensible space, building materials, topography, vegetation, and more, to predict which properties are most likely to experience a wildfire and which ones will survive.

Why Kin Chose Z-FIRE to Support Responsible Growth

Michael McCright, vice president, pricing and risk management at Kin, said:

“California requires a smarter, more modern approach to home insurance risk management. ZestyAI’s Z-FIRE model brings the level of insight we need to confidently assess risk and offer coverage in areas at risk of wildfire.”

“Kin’s expansion into California is exactly the kind of forward-thinking move our technology was built to support,” said Attila Toth, Founder and CEO of ZestyAI. “Together, we’re helping show that with the right data and tools, insurers can re-enter challenging markets with confidence—and deliver meaningful protection to homeowners who need it most.”

“Equally important, Z-FIRE empowers insurers to recognize and reward mitigation efforts at the property level, encouraging homeowners to take action that reduces risk for themselves and their communities.”

Real-World Performance: Z-FIRE in the Los Angeles Wildfires

Z-FIRE’s performance has been validated through real-world events: Following the recent Los Angeles wildfires, Z-FIRE’s highest-risk ratings closely corresponded with the hardest-hit areas, with 94% and 87% of the areas affected by the Palisades and Eaton fires rated as High Risk by the model.

Among homes located within these perimeters, those flagged as having the highest vulnerability to damage were 50% more likely to be destroyed—highlighting the critical value of property-specific insights, even in dense urban settings.

ZestyAI works closely with regulators to ensure transparency, validation, and continuous monitoring of its AI-driven models.

The company has secured regulatory approvals across all Western states for Z-FIRE, along with broad acceptance of its severe convective storm suite of models in Texas, Colorado, the Midwest, and the Great Plains.

The Michigan Department of Insurance and Financial Services has approved ZestyAI's Severe Convective Storm suite, including the proprietary Z-HAIL™, Z-WIND™, and Z-STORM™ models.

Michigan Faces Rising Losses From Severe Convective Storms

The approval comes as Michigan contends with rising weather-related insurance losses.

According to NOAA’s National Centers for Environmental Information (NCEI), the state has experienced over $5 billion in insured storm damage since 2019, with hail and straight-line winds accounting for the majority of claims. In 2024, a series of intense summer storms alone caused more than $1.2 billion in insured losses.

Why Carriers Need Property-Level Precision

ZestyAI’s AI-driven platform predicts the likelihood and severity of claims from severe convective storms at the individual property level by analyzing the interaction of local climatology with property-specific characteristics. In contrast, most risk assessment models today rely on broader territory or ZIP code-level evaluations, overlooking critical property-level factors. 

Each model is built and validated on extensive real-world claims data and delivers transparent explanations of the key drivers behind every risk score, helping carriers make more accurate underwriting and rating decisions.

How ZestyAI’s Storm Models Improve Risk Assessment

Key capabilities include:

• 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 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.

What Michigan’s Approval Means for Insurers

“As severe weather becomes more frequent and costly, insurers need tools that keep pace with evolving risks,” said Bryan Rehor, Director of Regulatory Affairs at ZestyAI.

“This approval gives Michigan carriers access to precise, property-level insights that support smarter underwriting and help reduce preventable losses.”

Michigan's approval marks the 17th state to embrace ZestyAI's Severe Convective Storm suite, reflecting increasing regulatory confidence in AI-powered risk models that deliver actionable insights while supporting industry-wide resilience efforts.