Reports & Research

Wildfire risk in the United States is no longer confined to the edges of forests or traditionally high-risk zones. New analysis using ZestyAI’s property-level wildfire models shows that millions of homes classified as low or no wildfire risk under federal assessments face elevated wildfire danger when evaluated at the property level.

This analysis was recently featured in Vox, which examined how wildfire behavior is evolving — and why broad, backward-looking risk maps are increasingly misaligned with how fires spread today.

👉 Read the full article on Vox → https://www.vox.com/climate/476932/california-wildfire-los-angeles-risk-ai-housing-climate

Wildfire risk is closer — and more granular — than most maps show

Many homes damaged or destroyed in the 2025 Los Angeles wildfires were still classified as “low risk” under federal wildfire assessments. ZestyAI’s property-level analysis provides a different perspective.

By evaluating individual structures — including vegetation proximity, defensible space, building characteristics, and neighborhood-level fire dynamics — ZestyAI identified more than 3,000 properties worth approximately $2.4 billion in areas impacted by the Palisades and Eaton fires that showed elevated wildfire risk despite being classified as low or no risk under FEMA’s census-level assessments.

Across California, the classification gap is even broader. Approximately 1.2 million properties, representing roughly $940 billion in residential property value, are designated as low or no wildfire risk under federal maps, despite AI-driven property-level models indicating elevated wildfire danger.

Why census-level wildfire maps fall short

Wildfires do not spread evenly across census tracts or counties. Ember-driven ignition, structure-to-structure spread, wind conditions, and localized vegetation patterns create uneven outcomes, where one home survives and the next is destroyed.

Federal wildfire assessments are designed to provide a baseline view of community-level risk. FEMA has noted that its National Risk Index is not intended to serve as a property-specific risk assessment. When risk is evaluated at the individual property level, meaningful differences emerge that aggregated maps are not designed to capture.

What more granular wildfire risk intelligence enables

More detailed wildfire risk data can support:

• Targeted mitigation efforts at the property and neighborhood level
• More informed rebuilding and land-use decisions
• Clearer, more defensible underwriting and portfolio strategies
• Improved dialogue between insurers, regulators, and communities

A shift in how wildfire risk is understood

Wildfire risk is evolving faster than the systems built to measure it. Homes are no longer just adjacent to wildfire hazards; they increasingly influence how fires ignite, spread, and intensify, even in dense urban environments.

Property-level risk intelligence does not remove hard decisions. But without it, those decisions are made using an incomplete picture of where wildfire risk truly exists.

Read the full Vox article here.

In property insurance, roof age is one of the most critical factors in assessing risk. Yet too often, carriers rely on self-reported or agent-supplied data that is incomplete or inaccurate.

ZestyAI’s recent analysis of 500,000+ properties revealed widespread discrepancies in reported roof age. The result? Mispriced policies, unexpected losses, and operational inefficiencies that impact the bottom line.

As climate volatility grows and reinsurance pressure intensifies, overlooking the true condition and age of a home’s largest, most exposed surface is a risk no carrier can afford.

What’s Inside

• Uncover the biggest myths and blind spots in roof age records.
• Understand why traditional data sources, like claims systems and permits, fall short in providing accurate roof age.
• Learn how a multi-source verification strategy, combining aerial imagery, permits, tax records, and AI, offers a blueprint for improvement and 97% national coverage.
• Explore why roof age is a predictor of losses across multiple perils, not just wind and hail.
• Discover the one-two punch of verified roof age and real-time condition insights, delivering a complete view of risk, even for young roofs with hidden problems.
• Align your roof age data with growing regulatory expectations, particularly in states like Florida.

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.

With insured losses projected to exceed $30 billion, the recent Los Angeles wildfires rank among the costliest in U.S. history—reshaping how insurers think about risk, resilience, and readiness.

Watch the Full Webinar → LA Fires in Focus: What Insurers Need to Know

In this on-demand webinar, experts from the Insurance Institute for Business & Home Safety (IBHS), the Western Fire Chiefs Association, Cal Poly’s WUI Fire Institute, and ZestyAI unpack what really happened—from frontline response to lab-based research and model performance—and share critical strategies insurers can use to prepare for what’s next.

Watch this session if you’re a Product Managers, Underwriters, Actuaries, and Risk & Innovation leaders looking to make informed decisions in an increasingly volatile wildfire landscape.

What You’ll Learn

• Key takeaways from the Los Angeles wildfires
• Research on structure-to-structure fire spread and resilience factors
• How wildfire risk models performed—what we got right (and wrong)
• Practical strategies to reduce exposure and strengthen resilience

Meet the Experts

• Anne Cope, Chief Engineer, IBHS
• Bob Roper, CEO, Western Fire Chiefs Association
• Frank Frievalt, Director, WUI Fire Institute at Cal Poly
• Kumar Duhvur, Co-Founder & CPO, ZestyAI

With insured losses projected to exceed $30 billion, the recent Los Angeles wildfires rank among the costliest in U.S. history—reshaping how insurers think about risk, resilience, and readiness.

Watch the Full Webinar → LA Fires in Focus: What Insurers Need to Know

In this on-demand webinar, experts from the Insurance Institute for Business & Home Safety (IBHS), the Western Fire Chiefs Association, Cal Poly’s WUI Fire Institute, and ZestyAI unpack what really happened—from frontline response to lab-based research and model performance—and share critical strategies insurers can use to prepare for what’s next.

Watch this session if you’re a Product Managers, Underwriters, Actuaries, and Risk & Innovation leaders looking to make informed decisions in an increasingly volatile wildfire landscape.

What You’ll Learn

• Key takeaways from the Los Angeles wildfires
• Research on structure-to-structure fire spread and resilience factors
• How wildfire risk models performed—what we got right (and wrong)
• Practical strategies to reduce exposure and strengthen resilience

Meet the Experts

• Anne Cope, Chief Engineer, IBHS
• Bob Roper, CEO, Western Fire Chiefs Association
• Frank Frievalt, Director, WUI Fire Institute at Cal Poly
• Kumar Duhvur, Co-Founder & CPO, ZestyAI

Wildfire Risk Is Rising Nationwide‍

Wildfire seasons are getting longer, more destructive, and harder to predict—and they’re no longer just a Western U.S. concern. From the Southeast to the Midwest, wildfire risk is emerging in places many insurers haven’t traditionally watched.

What the Latest Data Reveals About Wildfire Exposure

Drawing from the latest national datasets and insights from ZestyAI’s Z-FIRE™ model, this visual guide to wildfire risk in the U.S. shows:

• New wildfire hotspots: Discover where risk is rising fastest.
• Mitigation gaps: Learn how a lack of defensible space is putting thousands of homes in danger across the country.
• Top risk drivers: See how features like overhanging trees and wooden roofs are fueling destruction in high-risk areas.

Download Free Infographic

BONUS: You’ll also get access to our latest online event with IBHS and Western Fire Chiefs Association, The LA Fires in Focus: What Worked, What Didn’t, What’s Next for Insurers.

ZestyAI today announced an agreement with TruStage. This partnership will leverage ZestyAI’s suite of advanced property analytics solutions for valuable insights during commercial property underwriting.

TruStage will utilize three of ZestyAI's innovative property risk analytics models: Z-HAIL™, Z-FIRE™, and Z-PROPERTY™. Additionally, TruStage will use ZestyAI's Wildfire Mitigation Pre-Fill solution in response to new wildfire mitigation regulations set forth by the California Department of Insurance (CDI) with scalable, high-accuracy wildfire mitigation data without the need for expensive on-site inspections. 

“Global insured catastrophe claims are expected to top 100 billion dollars again this year, driven increasingly by secondary perils like hail and wildfire,” said Attila Toth, Founder and CEO of ZestyAI.

“By using AI‑driven, property‑specific intelligence instead of coarse territory‑level averages, TruStage can price risk more precisely, respond to California’s new wildfire mitigation requirements, and better protect its commercial policyholders.”

Z-HAIL is an AI-powered climate risk model that predicts the frequency and severity of hail claims for every property in the US. Z-HAIL examines the interaction of climatology, geography, and the unique characteristics of every structure and roof, including accumulated damage. This information can be used in both underwriting and rating at the time of quote. Using insights into a roof’s susceptibility to severe convective storms and the potential severity of those claims, insurers can accurately segment properties by risk level. 

In addition to Z-HAIL, TruStage will use ZestyAI’s Z-FIRE product, an AI-powered, predictive wildfire risk model built on decades of real insurer loss data, and ZestyAI’s Z-PROPERTY platform, which uses computer vision and machine learning to extract insights from aerial and satellite imagery, among other unique data sources, for over 150 million residential and commercial properties.

By leveraging multiple products on the ZestyAI Climate and Property Risk platform, TruStage is empowered to make informed and transparent risk decisions and deliver best-in-class services to its valued customers.

ZestyAI, the Risk and Decision Intelligence Platform for the insurance industry, today announced that its non-weather water risk model, Z-WATER™, has been reviewed and accepted for use in underwriting and rating in Illinois, Indiana, Iowa, Louisiana, and Wisconsin. 

Insurers in these states will now be able to set property-specific rates, align coverage with home-level vulnerabilities, and target inspections and mitigation strategies—including smart water sensors—to reduce cross-subsidization and improve portfolio performance.

Non-weather water has become a major pressure point for carriers, with losses now exceeding $13 billion annually and ranking as the third-costliest peril in homeowners insurance.

Routine failures like burst pipes and hidden leaks are now producing catastrophe-scale losses that surpass hurricanes in severity. Yet the peril has been difficult to model using traditional rating tools, which rely on territory-level or age-based proxies that overlook the property-specific factors driving interior water losses.

Using verified insurer loss data, Z-WATER applies computer vision to aerial imagery and incorporates property-level data, permitting history, localized climatology, and infrastructure context to capture the property-specific drivers of interior water losses. By modeling how these variables interact, Z-WATER predicts both the frequency and severity of non-weather water claims with up to 18× greater accuracy than traditional models.

Bryan Rehor, Director of Regulatory Strategy at ZestyAI, said:

“Non-weather water losses place real pressure on carriers’ books, but they’re also highly preventable when you understand where the risks actually lie.

Z-WATER helps insurers pinpoint those vulnerabilities at the property level and price them appropriately, while meeting regulators’ expectations for clarity and fairness.”

These approvals add to ZestyAI’s broader regulatory momentum. Across five perils—including wildfire, hail, wind, storm, and now non-weather water—ZestyAI has secured more than 80 approvals nationwide. Z-PROPERTY™, the company’s property and roof analytics solution, has also earned broad state-level approval, giving insurers and reinsurers trusted parcel-level insights with the same regulatory-grade transparency.

Most filing delays are self-inflicted; not by regulators, but by carriers submitting filings with missing pieces, unclear narratives, or outdated requirements. In prior-approval states, those slips don’t just slow things down; they can freeze millions in premium for months. That was the core message of ZestyAI’s recent webinar, Approval‑Ready: How Carriers and Regulators Can Accelerate Filings, featuring Carter Lawrence, Commissioner of the Tennessee Department of Commerce and Insurance, and Bryan Rehor, Director of Regulatory Strategy at ZestyAI. 

Watch the full session on demand here: Approval‑Ready: How Carriers and Regulators Can Accelerate Filings.

What regulators want from rate filings

Commissioner Lawrence opened with a simple reminder: regulators are people first, operating under clear statutory mandates but deeply focused on maintaining a healthy, competitive insurance market for the consumers they serve. 

For carriers, that means relationships and preparation matter. He urged companies to proactively meet with departments, especially before submitting novel products or complex filings that benefit from early discussion.​

Why filing delays cost insurers millions

From the carrier perspective, Bryan Rehor shared data from ZORRO Discover, ZestyAI’s agentic AI platform for competitive intelligence trained on hundreds of millions of pages of P&C filings, objection letters, and regulations. In prior‑approval states, ZORRO’s analysis shows that after the first objection, each additional objection typically adds about two months to the approval timeline, and incomplete responses can add another two to four months.​​

Those delays are often driven by preventable operational misses rather than disagreements over rate indications: missing actuarial exhibits, incomplete predictive model documentation, outdated checklists, procedural gaps, and under‑explained catastrophe assumptions. When ZestyAI’s team quantified the impact across lines, we estimated that delayed approvals translate into tens of millions of dollars per day in unrealized premium changes for the industry.​

How ZestyAI’s ZORRO Discover helps carriers become approval‑ready

The panel converged on a key idea: the industry needs to move from reactive, objection‑driven workflows to proactive, intelligence‑driven ones. For regulators, that means using technology to reduce low‑value manual review so teams can focus on complex judgment calls; for carriers, it means embedding regulatory awareness and quality checks directly into rate filing workflows.​

ZORRO Discover continuously ingests regulatory filings and related materials, so it flags gaps against current checklists, common objection themes, and emerging expectations in each state before a filing is submitted. Combined with ZestyAI’s regulator‑approved peril models and rate service organization capabilities, carriers can submit more transparent, thoroughly supported filings that earn trust and move faster through regulatory review.​​

FAQs: approval‑ready insurance filings and ZORRO Discover

What is ZORRO Discover from ZestyAI?‍

ZORRO Discover is ZestyAI’s agentic AI platform for competitive and regulatory intelligence in P&C. It analyzes 2M+ SERFF filings and related materials across all 50 states, turning millions of pages into real-time, citation-backed insights. For regulatory teams, it surfaces objection patterns and regulator expectations upfront, improving research efficiency by 20X. This helps teams run faster and more accurate pre-submission QA, draft cleaner filings, accelerate approvals, and reduce adverse selection.

How can insurance-specific AI reduce filing objections?‍

Agentic AI platforms for competitive intelligence, such as ZORRO Discover, scan millions of filings and related materials, including checklists, statutes, and historic objection letters. They help teams flag missing actuarial support, outdated checklists, weak justifications, and documentation gaps before submission. This “pre‑flight” QA reduces procedural errors that trigger avoidable objections and multi‑month delays.​​

How does ZestyAI help carriers be "approval-ready”?‍

ZestyAI helps carriers be approval-ready by strengthening both the models they file and the way those filings are prepared. Our peril models are filed through a Rate Service Organization (RSO) with standardized, regulator-tested documentation and a growing track record of approvals that carriers can reference as precedent. On the process side, ZORRO Discover provides pre-submission QA using regulatory objections and competitive insights. Together, this gives carriers more complete, regulator-aligned filings, fewer avoidable objections, and faster, more predictable approval timelines.

Why do prior‑approval states create unique challenges?‍

In prior‑approval states, rate and product changes cannot take effect until they are signed off by the Department of Insurance (DOI), so each objection round adds real financial cost as actuarially indicated changes sit idle. ZORRO Discover’s analysis shows that every additional objection can add months to the timeline, making operational quality and proactive compliance crucial levers for profitability.​

How does ZestyAI support regulators and carriers at the same time?‍

ZestyAI reduces friction on both sides of the filing process by providing regulators with better documentation and helping carriers.

For regulators:

• Standardized, RSO-filed model documentation that’s easy to review.
• Regulatory precedent from prior approvals, reducing model-review burden.
• Clear, transparent methodology aligned with statutory expectations.

For carriers:

• Faster approvals by referencing ZestyAI’s existing model approvals.
• Fewer avoidable objections through ZORRO Discover’s QA and objection-pattern insights.
• More complete, regulator-aligned filings with clearer documentation and rationale.
  

Outcome:
Regulators receive fully documented, RSO-filed models that are easier to review and validate. Carriers benefit from two advantages:

1. Clear insight into regulatory expectations to help them avoid common filing errors.
2. The ability to reference ZestyAI’s existing model approvals, which provides regulatory precedent and helps their own filings move through review more quickly.

Together, this reduces avoidable objections and creates a more efficient, predictable approval process for both sides.

To hear directly from Commissioner Carter Lawrence and ZestyAI’s regulatory experts, watch the full webinar on demand: Approval‑Ready: How Carriers and Regulators Can Accelerate Filings

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For insurers evaluating new data partners, transparency isn’t just about the model. It’s about the process. And at ZestyAI, that process is shaped by people who’ve actually operated inside carrier environments. Former actuaries, underwriters, product leaders, and regulatory specialists built our platform with a deep understanding of how difficult it is to integrate new technology inside a regulated ecosystem.

From day one, carriers get immediate value: full portfolio scoring, access to our web application, and the ability to validate data, explore properties, and begin applying insights right away.

Working with ZestyAI means:

• Real carrier experience behind the platform, not outsider assumptions.
• Direct access to industry experts across actuarial, underwriting, and regulatory domains.
• Instant time-to-value, with portfolio scoring and platform access available at kickoff.
• A focus on ROI, with every step designed to deliver measurable impact quickly.

Here’s what that looks like in practice — from kickoff to full production.

ZestyAI’s Onboarding Process: From Kickoff to Deployment

ZestyAI provides a structured onboarding experience aligned with your goals, whether focused on underwriting, rating, or operational efficiency. After the kickoff meeting, we work through a clear sequence designed to move fast while staying aligned with internal governance and IT workflows:

• Define objectives and use cases
• Align on data needs and file structure
• Establish integration protocols (API or batch)
• Support internal testing and model validation
• Provide regulatory guidance for rating, underwriting, and filings (state-specific documentation, actuarial support)

Our approach emphasizes speed-to-value while ensuring the process fits cleanly within your organization’s governance, compliance, and operational requirements. We don’t just integrate a model; we drive measurable outcomes such as improved segmentation, faster quoting, and operational efficiency.

ZestyAI’s models are designed to support a wide range of underwriting and rating workflows. Whether carriers use raw scores, tier bands, or mitigation indicators, the outputs align naturally with existing processes and program designs.

Integration with Guidewire, Duck Creek, Cogitate, and Other Platforms

ZestyAI is platform-agnostic and supports integration with:

• Guidewire
• Duck Creek
• Cogitate
• Custom core systems and middleware

We provide configuration support via secure APIs, batch ingestion, or prefill mapping. Our scores can be embedded into workflows across underwriting, inspection triage, mitigation eligibility, and renewals.

Data Requirements for Pilots or Backtests

To initiate a pilot or backtest, we typically request a dataset that includes:

• Property address or coordinates
• Policy effective and expiration dates
• Claims history (dates, causes, amounts)

Additional fields—such as construction type, roof material, or occupancy—can enhance model matching or segmentation. We’ll review your available data and finalize the format before ingestion.

Batch Scoring, API Integration, and Z-VIEW Access

ZestyAI models can be accessed via:

• Batch processing – ideal for backtests, portfolio scoring, and operational refreshes
• Real-time APIs – for use at quote, renewal, or mid-term policy changes
• Z-VIEW web application – a no-integration option for viewing property scores, risk drivers, and imagery

We support REST API and SFTP-based workflows, depending on your system architecture and compliance requirements. Most carriers start with batch mode and transition to real-time as production expands.

Need to evaluate before integration? ZestyAI’s portfolio scoring option enables carriers to assess entire books of business—no IT lift required.

Technical and Regulatory Support for a Custom Onboarding Experience

We offer hands-on support throughout the onboarding process, including:

• Data mapping and API testing
• Documentation walkthroughs and QA
• Score interpretation and regulatory consulting
• Workflow and dashboard design

We also provide custom analytics—such as lift charts or correlation studies—to support actuarial, underwriting, and product stakeholders across your organization.

For carriers preparing for rating or filing workflows, we also provide full regulatory support, including:

• Filing exhibits and actuarial documentation
• Dislocation and rate-impact analyses
• ASOP-aligned model memos and methodology summaries
• State-specific guidance and responses to DOI questions

Our goal is to make onboarding smooth for every stakeholder—actuarial, underwriting, product, compliance, and regulatory.

Typical Timeline to Run a Pilot or Backtest

Most pilots or backtests are completed within 4 weeks, depending on data quality and scope. After receiving your dataset, we:

• Score policies using the relevant ZestyAI models
• Analyze performance across segments (e.g., lift by decile)
• Present findings and operational recommendations
• Compare portfolio to aggregated state baselines

More advanced use cases—like rating segmentation or mitigation tracking—may require slightly more time to align with stakeholders. Regardless of scope, we aim to deliver clear, actionable insights quickly.

ZestyAI today announced that the Departments of Insurance in West Virginia, Georgia, South Dakota, Montana, Oregon, and Utah have reviewed and accepted its Severe Convective Storm (SCS) risk models, including Z-HAIL™, Z-WIND™, and Z-STORM™, for use in carrier rate and rule filings.

With these additions, ZestyAI’s SCS Suite is now ready for use in 29 states, supporting rating, underwriting, and reinsurance decisions across the most storm-exposed regions in the country.

Meeting the Growing Need for Transparent Storm Risk Assessment

As severe convective storm losses exceed $40 billion for the third consecutive year, regulators and carriers are accelerating the shift toward transparent, property-level models that clearly show what drives hail and wind losses.

ZestyAI’s SCS Suite is trained and validated on verified carrier claims data and delivers clear explanations of the factors behind each property’s risk score. By analyzing how local climatology interacts with individual property characteristics, the platform predicts the likelihood and severity of hail and wind claims with far greater precision than traditional territory or ZIP code–based methods.

Property-Level Storm Risk Models

• Z-HAIL: Quantifies hail risk using property-level drivers—roof geometry, accumulated damage, and local climatology—to pinpoint the buildings at greatest likelihood of hail damage, even within the same area.
• Z-WIND: Analyzes wind risk using AI-driven 3D analysis of roof condition, complexity, and potential failure points —together with localized wind climatology—to determine which buildings are most susceptible to wind damage.
• 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.

Bryan Rehor, Director of Regulatory Affairs at ZestyAI, said:

“Carriers and regulators are aligned around the need for transparent, property-specific evaluation of hail and wind vulnerability. “These filings reinforce the shift toward models that clearly explain the drivers of storm loss and support compliant, defensible decisions.”

New Capability: Mitigation-Aware Scoring

ZestyAI recently introduced Mitigation-Aware Scoring, allowing insurers to update model inputs and risk scores in real time based on verified changes to property attributes, such as:

• upgrading or replacing roof materials
• remediating visible roof or property condition issues
• correcting inaccurate data (e.g., misclassified roof type)
• modeling the impact of planned upgrades

Mitigation-Aware Scoring extends capabilities already widely used in Z-FIRE™ and ensures a consistent, carrier-controlled approach to reflecting verified improvements across perils. The functionality strengthens rating accuracy, supports fairer underwriting decisions, and aligns with evolving regulatory expectations around transparency and mitigation recognition.

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