Insurance & Risk Analytics 2026Updated

List of Wildfire Risk Modeling Companies

Comprehensive database of companies specializing in wildfire catastrophe modeling, property-level risk scoring, and fire behavior simulation for insurance underwriting and portfolio management.

Available Data Fields

Company Name
Wildfire Model Name
Model Type
Geographic Coverage
Resolution Level
Regulatory Approvals
Key Perils Covered
Technology Stack
Data Sources
Headquarters
Founded Year
Target Customers

Data Preview

* Full data requires registration
CompanyModelTypeHeadquarters
Moody's RMSNorth America Wildfire HD v2.0Probabilistic CAT ModelNewark, NJ
VeriskFireLine / Wildfire CAT ModelProperty-Level Scoring + CATJersey City, NJ
Karen Clark & CompanyUS Wildfire Reference Model v3.0Physics-Based CAT ModelBoston, MA
ZestyAIZ-FIREAI Property-Level Risk ScoreSan Francisco, CA
PyrologixStochastic Wildfire SimulationHazard & Risk AssessmentMissoula, MT

100+ records available for download.

* Continue from free preview

The Wildfire Risk Modeling Landscape

Wildfire catastrophe modeling has become one of the fastest-evolving segments in insurance analytics. The 2017-2018 California wildfire seasons, the 2020 record-breaking fire year, and the devastating 2025 Los Angeles firestorm have fundamentally changed how insurers approach wildfire risk—shifting the industry from backward-looking actuarial tables to forward-looking probabilistic and AI-driven models.

Why Traditional Approaches Failed

Before modern wildfire CAT models, insurers relied on historical loss averages and simple wildfire hazard scores. This approach systematically underpriced risk in areas experiencing rapid vegetation change, drought intensification, and WUI (Wildland-Urban Interface) expansion. The result: insurer insolvencies, market exits from fire-prone states, and a growing protection gap.

Major Model Categories

Probabilistic Catastrophe Models
Companies like Moody's RMS, Verisk, and Karen Clark & Company offer full stochastic event sets with hundreds of thousands of simulated wildfire scenarios. These models estimate expected losses, tail risk, and return periods for portfolio-level decisions. Moody's RMS North America Wildfire HD v2.0, released in October 2024, explicitly simulates urban conflagration—the house-to-house fire spread that drove catastrophic losses in the LA fires.
AI-Driven Property-Level Scoring
ZestyAI's Z-FIRE and Cape Analytics use aerial imagery, machine learning, and property-specific features (roof material, defensible space, vegetation proximity) to produce granular risk scores. Z-FIRE is approved for rating in all major wildfire-prone states and is used by over one-third of California's insurance market.
Physics-Based Fire Behavior Models
Technosylva (acquired by Lockheed Martin in 2024), Pyrologix (now part of Vibrant Planet), and KatRisk simulate actual fire ignition, spread, and suppression dynamics using fuel maps, topography, and weather conditions.

Regulatory Tailwinds

California's 2025 regulatory changes eliminated longstanding restrictions on using catastrophe models for ratemaking. Insurers can now incorporate forward-looking models and reinsurance costs into pricing—a fundamental shift that has accelerated demand for approved wildfire CAT models. Moody's, Verisk, and KCC have all completed or submitted models for California Department of Insurance review.

Climate Change Integration

Leading models now incorporate climate projections. KCC's Wildfire Reference Model includes 9 climate change scenarios across 3 time horizons (2025, 2030, 2050). Kettle's AI platform ingests over 130 terabytes of satellite, weather, and real estate data to simulate millions of wildfire scenarios under changing climate conditions.

Frequently Asked Questions

Q.Which wildfire models are approved for ratemaking in California?

As of early 2025, Moody's RMS, Verisk, and Karen Clark & Company have completed or submitted their wildfire catastrophe models for review by the California Department of Insurance under the new PRID process. ZestyAI's Z-FIRE is also approved for rating and underwriting in wildfire-prone states. Our AI crawls regulatory filings and vendor announcements to provide the most current approval status.

Q.What is the difference between a CAT model and a property-level risk score?

Catastrophe models (from Moody's RMS, Verisk, KCC) simulate thousands to millions of wildfire scenarios to estimate portfolio-level expected losses and tail risk. Property-level scores (from ZestyAI, Cape Analytics) assess individual address risk using aerial imagery and AI. Many carriers use both: CAT models for pricing and capital allocation, property scores for individual underwriting decisions.

Q.How does the data handle companies that model multiple perils beyond wildfire?

Most catastrophe modeling firms cover multiple perils (hurricane, earthquake, flood, etc.). Our dataset captures each vendor's wildfire-specific capabilities, model names, and coverage details so you can compare their wildfire offerings directly without sorting through multi-peril product suites.

Q.Can I get data on newer startups and AI-native wildfire modelers?

Yes. The dataset includes both established CAT modeling firms and newer entrants like Kettle, Dryad Networks, OroraTech, and CLIMADA Technologies. When you request the full list, our AI crawls the latest funding announcements, product launches, and partnership deals to capture the full vendor landscape.