Directory of AI property risk and catastrophe modelling vendors

Fenris supplies instant applicant and policyholder insight to carriers, agencies, brokers, underwriters and the platforms serving them, returning up to forty data points from a name and address in under two seconds. Its interfaces prefill applications across personal auto, home and life plus small business commercial, verify licences and vehicle identifiers, assess property hazards and perils, and score applicants for propensity to buy and lifetime value. It draws on a proprietary repository covering more than 255 million adults, over 35 million small businesses and every United States property, with machine learning matching records and predicting behaviour.

Greater Than turns driving data into crash probability and climate impact scores for motor insurers, fleets, mobility providers and vehicle manufacturers. Its Enerfy models, protected by seven patents and trained on driving data collected since 2004, break behaviour into thousands of variables to build individual driver profiles it calls DriverDNAs, from which it predicts accident probability and expected cost per trip in real time. The company argues explicitly that the industry's conventional signals, harsh braking events and lagging indicators such as violations and crash history, do not predict crashes, and prices behaviour instead. Data arrives through an on board device, a smartphone application or existing connected vehicle feeds, and scores reach insurers directly or through a major policy administration platform.

Renew Risk builds catastrophe models purpose designed for renewable energy assets, which conventional models handle poorly because turbines now reaching 160 to 230 metres in deep offshore water did not exist when the historical loss record was created. Its models calculate the frequency and severity of financial losses from windstorm, hurricane, earthquake and severe convective storm, using large cloud simulations and machine learning alongside engineering science, and cover the United Kingdom and Ireland, Europe, Taiwan, Japan and the United States across offshore and onshore wind, solar, tidal and hydrogen. Buyers are insurers, reinsurers, brokers and banks who need to price risk, commit capacity and finance projects, alongside developers and asset managers. New models are produced in around nine months against industry timelines exceeding three years.

Property risk analytics firm founded by chief executive Attila Toth and built from inception around property level risk scoring rather than around software with models added later. Its models combine geospatial data, satellite and aerial imagery, enriched permit and parcel data, three dimensional roof intelligence, climate science and structural engineering to produce risk scores at individual address level across the United States. The portfolio covers wildfire (Z-FIRE), hail (Z-HAIL), wind (Z-WIND), an integrated severe convective storm model (Z-STORM), inland and pluvial flood beyond federal flood maps (Z-FLOOD), general property characteristics (Z-PROPERTY), and non weather water and fire perils. Z-FIRE was the first AI based wildfire model approved as part of a carrier rate filing by the California Department of Insurance, and is built on fire science and structure ignition research from the Insurance Institute for Business and Home Safety and trained on what the company describes as the industry's largest historical wildfire loss database, spanning two decades. Carriers insuring roughly 40 percent of the California homeowners market use it. The storm suite holds approvals across sixteen or more states. Z-VIEW is a browser application delivering scores, top risk drivers, aerial imagery and mitigation simulation for any address with no integration work. Named carriers include Heritage Insurance and NEXT Insurance, and the company is a Duck Creek partner. It states that its models helped carriers and insurers of last resort extend coverage to more than 511,000 previously uninsurable properties in 2024. Former Verisk chief executive Scott Stephenson joined its board in 2026.