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Research

Future-Proofing Insurance: How to Prepare for Intensifying Wildfire Seasons

As ZestyAI unveils its annual Wildfire Season Overview, we can see that insurers are in a pivotal position to navigate the ongoing threat.

The insurance industry has been grappling for years with the skyrocketing losses caused by wildfires. As ZestyAI unveils its annual Wildfire Season Overview, we can see that insurers are in a pivotal position to navigate the ongoing threat.

Wildfire Risk Isn’t Going Anywhere

While we are currently experiencing a brief reprieve from the wildfire devastation of the last few years, the ongoing threat of wildfire remains at an all-time high.

Extreme snow and rainfall across the West in 2023 have led to wetter-than-normal conditions that have acutely reduced the risk of wildfire. However, wetter conditions lead to vegetation growth, so despite 2023 presenting lower wildfire risk, the resulting vegetation accumulation, combined with persistent drought conditions in future years, will likely result in extremely high losses in the coming years. In fact, heavy rainfall has preceded many of the most severe wildfire years ever recorded in California.

Heavy rainfall has preceded many of the most severe wildfire years ever recorded in California.
vegetation change map

Preparing for Future Wildfire Seasons

With high wildfire activity on the horizon, what steps can insurance companies take now to prepare for future wildfire seasons?

Here are three essential strategies:

1. Leverage Data for Better Understanding

Research by ZestyAI reveals that wildfires ravage 87% more land during drought years compared to non-drought years. With the western US still experiencing a megadrought that is the worst in over a millennium, it’s critical to understand the data and risks involved.

Not all homes face high risk. For the remainder, detailed property risk insights can highlight areas requiring risk mitigation. Integrate property-specific wildfire risk data into the underwriting and renewal process. This year is also an excellent opportunity to review a complete portfolio using an AI-powered wildfire risk assessment tool like Z-FIRE.

2. Educate and Empower Property Owners Through Transparency

Technology, particularly satellite/aerial imagery and artificial intelligence, can shed light on wildfire risks. Insurers can use this technology to assess the risk reduction measures that policyholders have implemented and understand how a property might withstand a wildfire.

This information is invaluable for educating homeowners and insurance agents. By knowing the specific actions that can be taken to reduce risk, such as clearing brush or using fire-resistant materials, both insurers and homeowners can be better prepared for wildfires.

3. Choose a Technology Partner Wisely

ZestyAI's Z-FIRE has set a benchmark by integrating loss data from over 1,500 wildfires and employing cutting-edge technology to derive insights on each property. By combining aerial and satellite imagery with machine learning and cloud computing, ZestyAI created Z-FIRE, a highly detailed wildfire risk assessment model.

Z-FIRE has been adopted by leading insurance carriers in every single western US state.

In 2022, Z-FIRE demonstrated remarkable performance. Its integration of data through machine learning and computer vision models has established Z-FIRE as a potent tool in wildfire risk assessment for both underwriting and rating.

z-fire adoption map in united states

Make Informed Decisions with Z-FIRE

Using Z-FIRE, insurance carriers, MGAs, and reinsurers can get access to actionable insights developed from detailed property-level risk factors. While wildfire losses may be inevitable, understanding in detail how individual properties contribute to average and tail risks is a large step forward.

The specific time and location of a wildfire is nearly impossible to predict. However, Z-FIRE can give carriers an assessment of the preconditions for that fire, and describe in detail the factors which contribute to it. Knowing, not guessing, which properties fall into a high-risk category is more important now than ever. We look forward to helping our customers through this fire season and many to come.

Z-FIRE Stands Alone in Compliance

Z-FIRE has been developed in partnership with top carriers and has been included in successful filings in California and many other western states. As regulators continue to push for additional transparency and accuracy in how insurers treat wildfire risk, AI-powered solutions provide a clear advantage because of their interpretability and sensitivity to changing conditions.

In 2023, California began requiring insurers to provide discounts based on mitigation measures, and in 2024 Oregon is poised to establish similar requirements on communications to homeowners. All of these changes create a burden on insurers, but those who can adapt to the new regulatory environment by leveraging knowledgeable partners like ZestyAI will have an advantage over competitors. AI is part of the solution, helping address climate risk and maintaining the insurability of properties across the US.

 

Download ZestyAI's 2023 Wildfire Season Overview 

Research

2023 Wildfire Season Overview: The Calm Before the Storm

ZestyAI has released its annual Wildfire Season Overview for 2023. This comprehensive report provides insights to assist insurers in effectively managing wildfire risk.

ZestyAI has released its annual Wildfire Season Overview for 2023. This comprehensive report combines insights from recent wildfire events, prevailing drought conditions, and cutting-edge advancements in artificial intelligence to assist insurers in effectively managing wildfire risk.

Download ZestyAI's 2023 Wildfire Season Overview

 

Here are some key findings from the report:

A Chance To Prepare While Wildfire Fuels Accumulate

Despite a brief respite from recent wildfire devastation, the current threat remains high. Over the past decade, wildfire risk has notably increased, particularly in California. However, the occurrence of extreme snow and rainfall in the West during 2023 has temporarily reduced the risk due to wetter conditions.

It's important to note that vegetation accumulation and ongoing droughts will likely lead to substantial losses in the coming years. California remains highly susceptible to losses and significant vegetation growth. This temporary relief in 2023 creates an ideal opportunity for insurers to review the risk technologies they have in place and embrace innovative solutions to prevent future losses.

No Role for Drought in Underwriting

Drought is indicative of fire intensity, but not losses. Although drought is an important factor in seasonal wildfire risk, the presence of drought shouldn't drive underwriting. Instead, insurers should look at property-specific solutions that consider wildfire risk over the lifetime of a policy.

Research has shown that this year's heavy rainfall may be a leading indicator for severe wildfire years to come. A comprehensive understanding of buildings, vegetation, and mitigation methods at the property level is necessary to effectively manage future wildfire risk.

A comprehensive understanding of buildings, vegetation, and mitigation methods at the property level is necessary to effectively manage future wildfire risk.

Using Advanced Models to Adapt to Changing Risks & Regulations

AI-powered risk models play a key role in mitigation. Insurers who write business in wildfire states have found increasing value in AI-powered wildfire risk models as they offer actionable risk insights, adapt quickly to changing climate risks, and comply with all regulations.

Over the last year, several western states have begun to implement new regulations for insurers in response to the changing risk environment. Discounts and transparency for mitigation efforts and property-specific decisions may become an industry standard as they have in California and Oregon.

What This Means for Insurers

In evaluating wildfire risk, many analyses tend to focus on the number of fires and the size of the area they burn. However, what really matters to insurance companies and property owners is the loss of structures and what can be done to mitigate those losses.

For example, those providing insurance in California might be surprised to learn that despite smaller losses in 2022 compared to 2021, the total national count of acres burned and fires ignited in 2022 actually exceeded that of 2021. This mismatch between yearly wildfire activity and the number of structures lost suggests that wildfire losses are not simply dictated by wildfire activity.

The most significant factor is not how many fires start, or how far they spread, but the potential resilience of every structure and what the communities and homeowners have done to prepare for wildfire exposure. Research from ZestyAI and IBHS shows that for a more precise understanding of potential losses, insurers need to zoom in on individual properties. They should consider a structure’s location, building materials, surrounding vegetation, and efforts taken by the surrounding community to prepare for wildfires.

Modern wildfire risk tools like ZestyAI's Z-FIRE do just that. They analyze individual property features and measure the impact of those features on the probability of loss. They also factor in nearby vegetation, community preparations, local infrastructure, and the lay of the land. This property-centric approach doesn’t try to predict exactly what a wildfire will do. Instead, it gives valuable information on how and why properties might be damaged by wildfires.

These models don't just offer a simple risk score, but also help explain what makes a particular property vulnerable and what steps can be taken to protect it.

 
Find out more, including how Z-FIRE performed in 2022, in this year’s Wildfire Season Overview.


Download ZestyAI's 2023 Wildfire Season Overview

Research

As Hail Damage Continues Across the U.S., New Research From ZestyAI and IBHS Works to Make Hail Losses More Predictable

Research considers valuable data on smaller hailstone impacts, which are likely responsible for 99 percent of the impacts on a roof from a hailstorm.

San Francisco, CA, April 19, 2023 – Today ZestyAI, the leading provider of climate and property risk analytics solutions powered by artificial intelligence (AI), and the Insurance Institute for Business & Home Safety (IBHS) released new research examining catastrophic losses from severe convective storms, particularly hail. The study focuses on hail-driven losses in property and casualty insurance.  

Hail losses are a persistent problem for property insurers’ risk management efforts. Historically, carriers have focused on intense events to predict hail risk, with supporting data confined to storms with hailstones larger than one or two inches. The study Small Hail, Big Problems, New Approach shows high concentrations of small hail are more important than previously thought, pointing to an opportunity to broaden data sets to account for the cumulative effect all hailstorms have on a roof’s susceptibility to damage over time, leading to a claim. 

This new research shows all hail needs to be accounted for when modeling and ultimately understanding losses. Using data from all hail events, not just those with hail that meet the severe criteria of one inch or greater, allows carriers to consider valuable data on smaller hailstone impacts. Additionally, insurers can integrate climate and materials science to better understand hail frequency and severity. Research suggests using this new approach could perform as much as 58 times more accurately than looking at events with large and very large maximum hail sizes alone, allowing carriers to more effectively assess hail risk, achieve more profitable underwriting and open up ratings to previously avoided areas.  

“As we’ve learned more about hailstorms, we've discovered storms that produce large concentrations of small hail are more common than we thought, and despite causing less individual damage than a single large hailstone, small hail, especially in high concentrations, is likely a meaningful contributor to the loss we see each year from hail,” said Dr. Ian Giammanco, managing director of standards and data analytics at IBHS. “Experiments also show large concentrations of smaller hailstones cause degradation to the asphalt shingles, specifically dislodging large amounts of granules. Once enough granules are lost, the underlying asphalt material can become more susceptible to aging and weathering. Repeated exposure to these types of hailstorms can shorten the life of an asphalt shingle roof and increase the damage caused by large hailstones in the next storm.” 

“Hail losses are a persistent problem for property insurers’ risk management efforts,” said Attila Toth, founder and CEO of ZestyAI. “Three of the nation’s five largest publicly-traded P&C carriers mentioned hail as a key concern in 2022 financial reports. Greater losses have brought attention to hail risk, and the insurance industry needs better approaches to solve this problem.” 

“Three of the nation’s five largest publicly-traded P&C carriers mentioned hail as a key concern in 2022 financial reports. Greater losses have brought attention to hail risk, and the insurance industry needs better approaches to solve this problem.” 

Hail risk can be especially costly to insurers because, unlike other catastrophic perils like hurricanes and wildfires, it can be difficult to identify the storm that caused a hail claim. As a result, insurance carriers could be forced to raise overall premiums or introduce high deductibles to compensate for the added costs.

As climate and materials science have developed, more data has become available providing  improved hail risk evaluation options that can lead to better decisions at earlier stages of the policy life cycle. Other benefits could include more profitable underwriting, a greater ability to rate previously-avoided areas and significantly reduced loss ratios.

For the complete ZestyAI and IBHS research paper visit this page.
 

About ZestyAI

ZestyAI offers insurers and real estate companies access to precise intelligence about every property in North America. The company uses AI, including computer vision, to build a digital twin for every building across the country, encompassing 200 billion property insights accounting for all details that could impact a property’s value and associated risks, including the potential impact of natural disasters. Visit zesty.ai for more information. 

About the Insurance Institute for Business & Home Safety (IBHS)

The IBHS mission is to conduct objective, scientific research to identify and promote effective actions that strengthen homes, businesses and communities against natural disasters and other causes of loss. Learn more about IBHS at ibhs.org

 

### 

  

For more information, contact:

Linsey Flannery

Director of Communications, ZestyAI 

linsey@zesty.ai 

416-939-9773 

 

Mary Anne Byrd

Communications Director, IBHS

mbyrd@ibhs.org

803-669-4216 

Research

90-Second Fact Sheet: The Reinsurance Market in 2023

Reinsurance rates are spiking to an all-time high. Fitch estimated a 20-60% rate increase for cedants in the overall property reinsurance market at the January 1st renewals.1 Terms and conditions are also tightening - many reinsurers are limiting their cedants to much higher attachment points2, or exiting CAT-exposed lines altogether

The main drivers for uptick in reinsurance rates

Our research has found three drivers underpinning the trend:

1. Devastating CAT losses, particularly from secondary perils

59% of all CAT losses come from secondary perils3, and those losses have caused major shifts in the reinsurance landscape. Howden estimates that global property CAT reinsurance rates were up 37% at the January renewals4.

2. A new urgency to improve return on capital

“When the cost of capital is equal to the rate of return, something has to change.” - Aditya Dutt, CEO of Aeolus Capital Management5. The reinsurance industry has underperformed since 2017, with an average return on equity of just under 5%6. Poor underwriting performance was a key driver, with an industry average 101% combined ratio over the same period7. Reinsurers are poised to use the tightening market as a chance to improve performance, with Fitch forecasting a 4pp underwriting margin expansion for reinsurers in 20238. Unfortunately for primary insurers, Goldman Sachs predicts that the same tightening market will create significant volatility for cedants9.

3. Value erosion in reinsurer investment portfolios

Macroeconomic factors are driving significant unrealized investment losses for reinsurers, particularly on fixed income portfolios due to rising interest rates. Aon estimates that these investment portfolio losses drove a 17% decline in global reinsurance capital across the first 9 months of 2022, with some players reporting equity value losses as high as 40-50% over that period10. Reinsurers will look to shore up these losses with better underwriting performance, which likely means tougher rates for primary carriers.

How property insurers can improve their odds with AI-powered predictive climate and property risk platforms

These factors mean that primary insurers can expect challenging reinsurance negotiations at the June 1st renewal deadline, particularly on property lines. However, new AI-powered predictive climate and property risk platforms can improve the odds for property insurers in three areas:

1. Rapid improvements in risk mitigation

Implementation-free portfolio reviews can quickly drive major loss ratio improvements.

2. Turn the tables of CAT risk screening in your favor

Improving data quality can lead to more favorable stochastic model portfolio screens, particularly with insight about the roof.

3. Enter the room as a leader in cutting-edge risk practices

Showing the same commitment to new technologies as industry leaders can help cedants build a better case.

Conclusion

With the right mitigation action and a cutting edge view of portfolio risk, cedants can navigate the upcoming 6/1 renewal successfully.

Learn more about how an AI-powered predictive climate and property risk platform can help you.

 

 

 

 

 

------------------------------------------------------------------------

Sources

1 & 8 - Fitch, Reinsurers’ Underwriting Margins to Expand by 4pp in 2023

2 & 3 - Gallagher Re, Gallagher Re Natural Catastrophe Report 2022

4 - Howden, Howden’s renewal report at 1.1.2023: The Great Realignment

5 - AM Best, Reinsurance: Roundtable Discussion on Renewals and What 2023 May Hold

6, 7 & 10 - AON, Reinsurance Market Dynamics

9 -  Reinsurance News, Hard market to increase volatility for primary insurers: Goldman Sachs

Research

ZestyAI Announces 180-day Playbook to Navigate First-of-its-kind Wildfire Regulatory Requirements in California

Playbook Leverages Historic Regulatory Success of ZestyAI’s Wildfire Model (Z-FIRE™) to Lead Insurance Carriers Towards Regulatory Compliance in the Largest Insurance Market in the U.S.

San Francisco, CA, September 20, 2022 – ZestyAI, the leading provider of property risk analytics solutions powered by Artificial Intelligence (AI), has developed a 180-day playbook to support insurance carriers as they work to meet the Mitigation in Rating Plans and Wildfire Risk Models regulation expected to be adopted by the California Department of Insurance (CDI) before year-end. The playbook reflects the company’s unique ability as the only comprehensive solution in the marketplace to help insurers meet or exceed every single requirement in the new regulation — meeting 100 percent compliance inside the tight 180-day window.

On September 7, 2022, Insurance Commissioner Ricardo Lara announced he had submitted the department’s insurance rating regulation recognizing wildfire and safety mitigation efforts made by homeowners and businesses, to the California Office of Administrative Law for final approval. This first-of-its-kind regulation will require all insurers in California to refile their existing rating plans on an aggressive 180-day timeline. 

“Eight of the ten most destructive wildfires in California’s history have occurred in the last five years,” said Attila Toth, Founder and CEO of ZestyAI. “While the new wildfire regulations will have a significant impact on California’s insurance industry, adapting to this peril is key to having a sustainable insurance ecosystem in California. As the leader in property-specific wildfire risk assessment, we have offered input at each step of this process. We are here to support admitted carriers with a turnkey solution complying with every single requirement as they navigate this process and work to meet the new regulations.”

The new wildfire safety regulation requires insurance companies to consider the structure of a home, its surroundings, and community-level mitigation. Insurers with concerns about the regulation can reach out to ZestyAI to get a complete explanation of how the regulations will impact them. This includes access to the 180-day playbook, which breaks down the regulatory compliance process into an orderly roadmap that addresses all three major challenges that insurers will face:

  • Operational — The process of rapidly integrating new data sources, educating the public on how wildfire mitigation affects insurance policies, and a framework for a compliant appeals process.
  • Rating — How to weight property-specific characteristics, including those with and without historical loss data, in rating plans as well as guidance on mitigation credits.
  • Filing — Carriers who use a rating plan reliant on traditional wildfire models without property-specific information will need to overhaul their rating framework. Relying on multiple approved rate filings, ZestyAI has developed a comprehensive filing toolkit that can support carriers at every facet of the filing process.

ZestyAI’s Z-FIRE™ model has quickly become the leader in property-specific wildfire risk assessment. Using AI algorithms trained on more than 1,500 wildfire events across 20 years of historical loss data, Z-FIRE™ provides a level of detail that is of essential value to both the insurer and the homeowner.

The model was the first AI model ever approved as part of a rate filing by the CDI and the second wildfire risk model. It has been widely adopted across the Western U.S., where its use has been approved for both underwriting and rating. During 2021's APCIA Western Region Conference, CDI representatives expressed that the agency’s familiarity with Z-FIRE™  means in future filings the focus will be limited to the carrier's specific use of the model, not the details of the model itself, potentially greatly expediting the reviews of carriers using the Z-FIRE™ model.

ZestyAI’s Z-FIRE™ considers features such as topography and historical climate data in combination with factors extracted from high-resolution imagery of the property itself and its surroundings, including homeowner and community mitigation efforts, to provide both neighborhood and property-specific risk scores. 

A significant advantage to insurance carriers is that they can use these data elements to communicate with homeowners on what specific actions can be taken to lower their property’s risk, such as upgrading building materials and cutting down surrounding dry brush or overhanging vegetation. The impact of mitigation efforts can be significant. A joint study by the Insurance Institute for Business & Home Safety (IBHS) and ZestyAI, which studied over 71,100 wildfire-exposed properties, found that property owners who clear vegetation from the perimeter of their home or building can nearly double their structure's likelihood of surviving a wildfire.

 

About ZestyAI

ZestyAI offers insurers and real estate companies access to precise intelligence about every property in the United States. The company uses AI, including computer vision, to build a digital twin for every building across the country, encompassing 200 billion property insights accounting for all details that could impact a property’s value and associated risks, including the potential impact of natural disasters. Visit zesty.ai for more information.

Research

ZestyAI Publishes Data-Driven Look at 2022 Wildfire Season

2022 Wildfire Season Overview looks back at 2021 and ahead to what may be a long year of wildfires in 2022.

Download Report

Today, ZestyAI released its 2022 Wildfire Season Overview. Each year, ZestyAI prepares a comprehensive overview to help guide insurers based on recent wildfire events, persistent drought conditions, and advancements in artificial intelligence for managing wildfire risk.

If it seems like wildfires are burning at all times of the year, it's not just you. Very destructive events, like last December's Marshall Fire, are occurring in months not typically associated with high wildfire danger. Those who study wildfires, including ZestyAI, have begun to start thinking in wildfire "years" instead of wildfire "seasons'. Strong wildfire years, with 10+ million acres burned, have quickly become the new normal. The last 10 years have been the worst on record for property and casualty (P&C) insurers when it comes to wildfire. 8 of the top 20 fires in California history, and more than half of the acreage burned by them, occurred in just the years 2020 and 2021.

What can insurers do to prepare themselves for persistent wildfires?

  • Understand the Data: Instead of sticking with decades-old approaches, assess wildfire risk at the property level.
  • Continue to Bring Transparency and Education to Homeowners: Insights from AI-based wildfire risk models may be passed on to homeowners and agents, enabling a much better understanding of wildfire risk.
  • Find the Right Technology Partner: Aerial and satellite imagery, machine learning, and infinitely scalable cloud computing resources were combined to build the most granular wildfire risk assessment model (Z-FIRE™). Using Z-FIRE™, ZestyAI can accurately estimate an individual property’s wildfire risk, plus highlight the key property-level factors that contribute to that risk.

Click here to download ZestyAI's 2022 Wildfire Season Overview.

ZestyAI offers insurers and real estate companies access to precise intelligence about every property in North America. The company uses AI, including computer vision, to build a digital twin for every building in North America, encompassing 200B property insights accounting for all details that could impact a property’s value and associated risks, including the potential impact of natural disasters. Visit https://zesty.ai for more information.

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Press Room

TruStage Partners with ZestyAI for Commercial Property Analytics Solution

TruStage implements ZestyAI’s suite of climate risk solutions for underwriting insights and to help respond to wildfire regulations in California

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.

Press Room

ZestyAI’s Z-WATER™ Greenlit in Five States as Non-Weather Water Losses Intensify

Regulators Review and Accept AI Model Addressing $13B in Annual Non-Weather Water Losses

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.

Blog

Becoming “Approval‑Ready”

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

Blog

From Pilot to Production: What It’s Like to Work with ZestyAI

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.

Press Room

ZestyAI Expands Regulatory Footprint for Its Severe Convective Storm Suite Across Six States

As SCS losses surpass $40B for the third year in a row, regulators in West Virginia, Georgia, South Dakota, Montana, Oregon, and Utah review and accept AI-driven, property-level storm risk models.

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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