Reports & Research

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.

The California Department of Insurance (CDI) has introduced significant updates as part of its Sustainable Insurance Strategy. These new bulletins and draft regulations aim to accelerate regulatory approvals, embrace forward-looking models, and address critical reinsurance challenges.

But what do these changes mean for insurance carriers—and how can you prepare?

On January 29, 2025, we hosted a webinar, California’s Evolving Insurance Landscape: The Future of Insurance in the Golden State. 

Designed for Legal & Compliance professionals, Product Managers, Underwriters, Actuaries, and Risk & Innovation leaders, the discussion featured expert insights from:

• Michael Peterson, Deputy Commissioner of Climate & Sustainability, California Department of Insurance
• Karen Collins, VP, Property & Environmental, APCIA
• Bryan Rehor, Head of Regulatory Affairs, ZestyAI

Missed the live event but want to gain actionable insights from industry leaders at the forefront of California’s insurance evolution? Watch on demand now!

Regulatory Ready: How to Use AI Responsibly in Insurance Under the NAIC Bulletin

AI innovation is revolutionizing the insurance industry, but with these advancements come new regulatory challenges. To ensure responsible use of AI in insurance, it’s essential to stay informed about the latest regulatory frameworks.

Join us on November 13 at 11 PT / 2 ET for an exclusive webinar where we’ll break down how to navigate AI regulations under the NAIC Model Bulletin.

In this session, led by

• Kevin Gaffney, Vermont’s Commissioner of Financial Regulation and Chair of the NAIC’s Innovation & Tech Committee
• Bryan Rehor, Director of Regulatory Strategy at ZestyAI

you'll gain critical insights on how to align AI usage with evolving regulatory expectations.

 
What You’ll Learn

This webinar will provide practical takeaways that can help insurance professionals understand and comply with the latest AI standards:

• NAIC Model Bulletin Overview: Understand the core principles behind the NAIC’s AI regulation framework.
• Ensuring AI Compliance: Learn how to ensure responsible AI usage according to NAIC standards.
• Preparing for Regulatory Oversight: Get ready for closer state-level inspections and regulatory scrutiny.
• Vendor & Partner Compliance: Ensure that your partners meet regulatory requirements for transparency and fairness.
• Interactive Q&A: Take advantage of the opportunity to ask our experts about the complex world of AI and insurance compliance.

Meet the Experts

Kevin Gaffney
Vermont Commissioner of Financial Regulation

As an expert in AI regulations and the NAIC’s Model Bulletin, Commissioner Gaffney will provide key insights into how insurance companies can effectively implement responsible AI practices. His experience in overseeing state-level financial regulation will offer attendees a unique perspective on aligning AI innovation with compliance.

Bryan Rehor
Director of Regulatory Strategy at ZestyAI

Bryan Rehor will offer practical advice on maintaining AI compliance while harnessing the full potential of AI innovation. His expertise lies in guiding insurers through regulatory demands, ensuring that AI practices meet industry standards while avoiding common pitfalls.

Why You Should Attend

This webinar is tailored for professionals in insurance, particularly those in Executive, Legal, Compliance, Product Management, Underwriting, Actuarial, Risk, and Innovation roles.

Whether you’re navigating the complexities of AI regulation or preparing for the next steps in compliance, this session will provide actionable insights to help you move forward confidently.

Bonus Content

By registering for the webinar, you’ll receive our interactive guide:

“When Innovation & Regulation Meet: What Insurers Need to Know About AI and Regulatory Compliance.”

This resource will deepen your understanding of how to stay compliant while leveraging the power of AI in your insurance operations.

 
Don’t miss out!
Register for the webinar and ensure your spot in this exclusive event.

Facing Unprecedented Climate Challenges

The insurance industry is facing unprecedented challenges as natural catastrophic events like convective storms and wildfires become more frequent and severe. Traditional risk models, which often rely on broad territory-based segmentation, are struggling to keep up with these dynamic environmental threats. This has led to significant financial losses for insurers, who are now seeking more accurate and proactive methods to predict and manage climate risk.

AI Adoption in Property and Casualty Insurance

To shed light on the adoption of these cutting-edge techniques, ZestyAI conducted a survey of over 200 executives in the Property and Casualty (P&C) insurance sector. The survey reveals which AI-based models are gaining traction, what features insurers prioritize, and how transparency and regulatory concerns are shaping the industry. It also highlights the specific risks that are top of mind for carriers today.

AI Transforming Risk Assessment Models

The industry is turning to AI-based risk assessment models that offer a new level of precision. Companies like ZestyAI are leading the charge, providing tools that enable insurers to assess risk on a property-by-property basis, considering both individual property features and their interaction with surrounding environmental factors. These advanced models are transforming the way insurers underwrite policies, optimize portfolios, and align coverage with actual needs.

Dive deeper into our findings and explore the full report by clicking below.

Access the Report
 

The Rising Threat of Severe Convective Storms

The past few decades have seen a dramatic rise in the frequency and intensity of severe convective storms, resulting in significant financial repercussions for the insurance industry. In the last year alone, insured losses from severe convective storms reached an astounding $60 billion, marking an average annual growth rate of over 11% over the past twenty years. This alarming trend means a new approach is needed to manage and mitigate the escalating risks associated with severe weather events.

In the last year alone, insured losses from severe convective storms reached an astounding $60B, marking an average annual growth rate of over 11% over the past twenty years.

The traditional methods of risk assessment and management are no longer sufficient to cope with the increasing unpredictability and severity of these weather events. As the risk evolves, so must the solutions. Changing risks call for innovative solutions that leverage advanced technology and data analytics to enhance the accuracy and effectiveness of risk modeling.

A New Approach

ZestyAI’s Z-HAIL and Z-WIND models are specifically designed to address the challenges posed by severe convective storms. In a new retroactive case study, we explore the performance of these models on a carrier’s book of business over the prior five years, highlighting their effectiveness in delivering comprehensive coverage and precise risk segmentation.

Key findings from the case study include:

Comprehensive Coverage with High Accuracy

One of the standout results from the case study is the exceptional hit rate of 99.7% achieved by Z-HAIL and Z-WIND. This shows the models were able to accurately identify and assess the risk of severe convective storms for nearly all the properties in the carrier's portfolio.

Strong Risk Segmentation

The models demonstrated remarkable capability in risk segmentation, with Z-HAIL generating a lift of 62X and Z-WIND achieving a lift of 9.7X. This means that the models were able to effectively differentiate between high-risk and low-risk properties, even within small geographic areas such as a single zip code. Accurate risk segmentation allows insurers to tailor their policies and pricing strategies more precisely, leading to better management of their risk exposure.

Improved Combined Ratio

Implementing Z-HAIL and Z-WIND would significantly enhance a carrier’s combined ratio, calculated to be approximately 4 points in the first year. This improvement can be attributed to the models’ ability to optimize underwriting, rating, and the application of deductibles and Actual Cash Value (ACV) endorsement strategies. By accurately assessing the risk and applying appropriate measures, insurers can reduce their loss ratios and improve overall profitability.

The Need for Innovative Solutions

As severe convective storms continue to pose significant challenges to the insurance industry, adopting innovative solutions like ZestyAI’s severe convective storm models can help insurers better manage this escalating risk.

These models provide comprehensive coverage, accurate risk segmentation, and improved financial performance. By embracing advanced technology and data-driven analytics, insurers can navigate the complexities of severe weather events and safeguard their portfolios against future losses.

To learn more about the detailed findings and benefits

Download the full case study.

Are rising storm costs and inaccurate roof assessments impacting your bottom line?

Now available to stream, The Science of Roof Risk master class will equip you with the latest strategies and techniques to master roof risk assessment.

• Enhance your roof risk assessment by 60X
• Improve your combined ratio
• Reduce storm-related roof claims
• Strengthen new business selection

What we cover:

Your presenters, Ross Martin (VP, Risk Analytics) and Sam Fetchero (Head of Marketing) will share with you:

• The Problem of the Roof:  Uncover the underlying factors driving rising storm losses and why traditional risk assessment methods fall short.
• The Science Behind Predicting Losses: Explore key factors impacting  roof risk and loss prediction, including roof age, condition, complexity, and peril-specific models.
• Accuracy-focused Risk Models: Discover advanced modeling techniques that enhance predictive accuracy.
• Understanding Storm Climatology: Learn how storm climatology impacts roof risk and how to integrate these insights into your risk assessment strategies.
• Real-World Results: Witness a comparative analysis of these predictive factors using actual carrier data. Understand the strengths and weaknesses of each approach.
• Priorities of Leading P&C Insurers: 
  See what your peers asked with valuable insights to take back to your team.

Who Should Watch?

This video is ideal for Executives, Product Managers, Actuaries, Underwriters, and CAT Modelers committed to enhancing their roof risk assessment capabilities. 

Bonus Guide

As a bonus for watching, you'll receive a downloadable study on the latest roof risk assessment strategies: Preparing for the Storm: The Insurers Guide to Roof Risk.

Access Now

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 announced that its Severe Convective Storm suite, including Z-HAIL™, Z-WIND™, and Z-STORM™, has received regulatory approval from the Ohio Department of Insurance.

With the addition of Ohio, ZestyAI’s Severe Convective Storm suite is now approved for use in 16 states, covering key high-risk markets across the Midwest, Great Plains, and South.

Ohio Faces Rapidly Rising Storm Losses

Ohio has experienced 36 billion-dollar loss storm events over the past five years alone, surpassing the total from the previous two decades, which saw just 33 events, according to NOAA’s National Centers for Environmental Information (NCEI). Severe convective storms, including hail, wind, and tornadoes, were the driver, contributing to over 57% of the state’s total weather-related damages since 1980.

Traditional Models Miss Critical Property-Level Differences

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.

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, examining the interaction between climatology and the unique characteristics of every structure and roof.

Regulatory Approval Reflects a Shift Toward Precision Underwriting

“Too often, storm risk is priced using rough proxies instead of accurate property insights,” said Kumar Dhuvur, Founder and Chief Product Officer at ZestyAI.

“Regulatory approval in Ohio affirms the industry’s shift toward precision underwriting and rating—and opens the door to smarter, risk-aligned decisions and fewer preventable losses in one of the nation’s most important insurance markets.

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.

ZestyAI helped carriers and insurers of last resort extend coverage to over 511,000 properties previously deemed uninsurable in 2024. This year, ZestyAI aims to double its impact, helping to bring coverage options to over a million families and businesses, ensuring that those in catastrophe-prone regions have access to sustainable, risk-aligned insurance.

A 2024 Deloitte survey found that nearly a quarter of homeowners in high-risk states are struggling to find coverage, while over half cite affordability as a growing concern—underscoring the industry’s need for granular insights that support underwriting and pricing decisions aligned with true property-level risk.

“For too long, insurers have had to make high-stakes decisions with incomplete information,” said Attila Toth, Founder and CEO of ZestyAI. “Advanced AI models are changing that. With granular, property-specific risk insights, insurers can close protection gaps and build a more resilient market.”

Traditional risk assessment methods rely on territory- or ZIP code-level evaluations, overlooking the property-level characteristics that drive risk. This approach leads to adverse selection, inaccurate pricing, and widespread market withdrawal.

ZestyAI replaces this approach with transparent, AI-powered models that integrate climatology, geospatial data, historical losses and structural attributes to deliver precise views of wildfire, hail, and wind risk, among other perils.

The results:

• Clear mitigation guidance to help policyholders take action.
• Risk-aligned premiums that support responsible market expansion.
• Improved underwriting precision through AI-driven risk scores and near-complete U.S. coverage.
• Optimized loss cost controls via more effective deductible, Actual Cash Value (ACV), and coverage strategies.
• A supportive experience for carriers, families, and businesses—enabling faster decisions, better communication, and greater confidence in coverage options.
• Streamlined inspections that lower expenses and improve efficiency.

ZestyAI collaborates closely with regulators to ensure transparency, validation, and model oversight. Its wildfire model, Z-FIRE, is approved across all Western states, while its severe convective storm models have gained broad acceptance from Texas to Colorado and throughout the Midwest and Great Plains.

As regulators support the use of advanced models, they are also paving the way for smarter risk-based pricing and proactive mitigation—revitalizing insurance’s core mission: protecting the livelihood of home and business owners and their communities.

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! 

ZestyAI has partnered with EarthDaily Analytics (EarthDaily), a global provider of Earth Observation analytics and data.

Through this partnership, ZestyAI’s advanced models—including Z-FIRE™, Z-HAIL™, Z-WIND™, and Z-STORM™—will be available through EarthDaily’s Ascend platform, delivering geospatial data, risk modeling, and post-event insights to insurers.

With the insurance industry facing escalating challenges from climate-driven catastrophes and increasing pressure to accurately price risk, ZestyAI’s models provide granular, property-level risk data. These models analyze factors like vegetation density, construction materials, and historical weather patterns to offer insights beyond traditional methods.

“At EarthDaily, we’re committed to delivering cutting-edge property insights to customers navigating today’s climate risks,” said Rachel Olney, VP of Insurance at EarthDaily.

With advanced AI models covering wildfire, hail, wind, and property data, ZestyAI is an ideal partner to support our mission.

"By including their advanced analytics in our Ascend platform, we’re excited to empower clients to take proactive steps in managing and mitigating risk with confidence."

ZestyAI’s solutions achieve nearly 100% hit rates, offering actionable insights that insurers and businesses can trust. By bolstering the data available in the Ascend platform with property-level insights, the partnership provides decision-makers with a new level of clarity to mitigate risks, improve underwriting, and allocate resources more effectively.

The collaboration exemplifies the growing importance of innovative technology in the insurance and property management sectors, especially as global climate risks continue to evolve.