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

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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