Commercial property insurer FM has acquired FortressFire, a wildfire intelligence company that combines machine learning with physics-based fire modeling. Financial terms were not disclosed.
FM, established nearly 200 years ago, insures many of the world's largest commercial and industrial properties. It counts one in four Fortune 500 companies among its policyholders and employs nearly 2,000 engineers across 14 countries. Its model is built around engineering-led loss prevention rather than risk transfer alone.
FortressFire fits that approach. Its platform goes beyond estimating fire probability to assess whether a specific structure will ignite, and what steps can prevent it. The company's outputs include aerial wildfire reports, ground inspections, monitoring, analytics, and mitigation assessments used by insurers, reinsurers, brokers, lenders, and property owners.
FM said FortressFire will operate as an independent, wholly owned division under its own brand and leadership.
The acquisition arrives as wildfire losses mount globally. Swiss Re Institute estimated global insured catastrophe losses reached $107 billion in 2025, with wildfires and severe storms accounting for 83% of that total. Investment in property-level analytics is accelerating in response.
More than 20 US states have accepted AI-driven wildfire models in rate filings, based on Insurance Institute for Business & Home Safety (IBHS) and American Property Casualty Insurance Association (APCIA) data. Regulators are moving in the same direction as carriers.
"FortressFire shares FM's core belief in the power of data-driven, location-based risk mitigation and protection measures to help clients better understand and manage wildfire exposure," said Malcolm Roberts, chairman and chief executive officer of FM.
Ashker, who founded FortressFire, said the company has long argued that ignition prevention is the basis of sound wildfire risk management. He added that the path to insurability runs through science.
The gap between carriers using coarse geographic risk segmentation and those with structure-level modeling is widening, with adverse selection pressure building on less sophisticated books.
For brokers, the FM-FortressFire deal is less significant than what it reflects about where the market is heading. Bringing a structure-specific wildfire platform in-house signals that FM intends to price fire-exposed commercial property with a precision that broader geographic models cannot match.
Carriers using coarser risk segmentation face a compounding problem. Granular pricers attract lower-risk properties at competitive rates, and less sophisticated books accumulate a disproportionate share of higher-risk accounts. That pattern is already reshaping which carriers can write profitably in fire-exposed markets.
Clients who document mitigation efforts are better positioned to access competitive terms. Cleared vegetation zones, structure hardening, and scheduled inspections are increasingly the inputs that separate a standard placement from a preferred one.
The deal reflects a broader consolidation trend in wildfire risk analytics. FutureProof Technologies bought wildfire modeling firm Terrafuse AI in November 2025 to expand into western markets where standard carriers have withdrawn. The pattern points to a market recognizing that fire risk at the property level requires data infrastructure, not just capacity.
The shift toward property-level wildfire analytics mirrors regulatory changes allowing more sophisticated models in rate filings across multiple states.
