Climate X, a provider of climate resilience analytics, has announced the launch of Global Wildfire, a global probabilistic wildfire model designed to help organisations assess and manage wildfire exposure at an asset level.
The company said increasing wildfire frequency and severity are creating challenges for organisations seeking accurate and consistent risk information. With Swiss Re estimating wildfire losses could reach $40bn in 2025, Climate X said many existing models do not provide the level of detail required to assess risk across diverse global portfolios.
Global Wildfire has been developed to provide insurers, asset managers and public sector organisations with detailed insights into wildfire exposure, enabling them to evaluate potential impacts and make informed decisions.
“Wildfires are a major risk management problem,” added Lukky Ahmed, Co-founder and CEO of Climate X. “For the first time, using Global Wildfire, Institutions have defensible, globally consistent, location-level analytics that translate hazard into potential loss.”
According to Climate X, the model provides a more detailed alternative to index-based and historical wildfire assessments by combining scientific modelling techniques with asset-level analysis. The company said Global Wildfire delivers risk outputs at a 30m (98ft) resolution, incorporating factors such as local landscape conditions, building characteristics and potential financial impacts.
The model can also be used to assess future wildfire scenarios through to 2100 across different climate pathways, helping organisations understand how exposure could develop under changing climate conditions.
“Global Wildfire is a significant step beyond index-led or purely historical approaches to wildfire risk,” added Ahmed. “We’re giving clients a way to move from hazard insight to real financial risk quantification leading to a more transparent, scientifically robust view that underwriting, credit risk and regulatory scenario analysis all demand.”
Global Wildfire covers 93% of global GDP across eight regions, allowing financial institutions to compare wildfire exposure across multiple markets using a consistent methodology. The company highlighted that many existing wildfire models have historically focused on specific high-risk regions, including the US and Australia, while global organisations often require comparable risk assessments across a wider range of locations.
The model generates absolute probabilistic burn probabilities rather than relative risk scores or qualitative rankings. The company said this provides organisations with measurable risk estimates and uncertainty ranges that can support investment reviews, portfolio analysis, stress testing, governance processes and financial modelling.
Global Wildfire uses machine learning trained on satellite data to assess local fire susceptibility, including factors such as terrain, vegetation and human influence within wildland-urban interface areas. Climate X said ignition risks are then combined with physical fire-spread simulations using cellular automata methods to model thousands of potential wildfire events for each location.
These simulations account for variations in ignition points, fire size and spread direction, providing organisations with a detailed view of potential wildfire impacts across their assets and portfolios.
