Navigating Consistency in Wildfire Risk Assessment
The Value of Consistent Probabilities in Responding to Complexity
Insurance actuaries do not need a perfect model of fire behavior; they need reliable, repeatable, and sufficiently precise probability assessments to price risk across a portfolio of policies. Athena’s strength is not in modeling the intricate physics of wildfire but in delivering consistent probabilities of wildfire damage based on a stable set of parameters.
Last week, Athena published this article about the complexity of wildfires and how we use Machine Learning to deal with the complexity.
This article covers the same topic, but with more focus on the role of portfolios and consistent probabilistic outcomes and why this is important for the correct valuation of risk. Wildfire risk has been studied extensively by data scientists, firefighters, and researchers seeking accuracy in fire behavior predictions. Their goal is to understand and explain the physics of wildfire — how it spreads, reacts to different environmental conditions, and behaves under varying circumstances. This is like evaluating and selecting individual stocks.
Athena Intelligence takes a different approach, which is more like thinking about index funds than selecting individual equities. Rather than striving for perfect accuracy in fire behavior modeling, Athena prioritizes consistent, commercially viable predictions of wildfire risk that are useful for decision-makers, particularly in the insurance and financial sectors.
The Value of Consistent Probabilities Over Complexity
Traditional wildfire models often struggle with the sheer complexity of fire dynamics, incorporating countless factors such as fuel loads, terrain, climate patterns, and human development. While complexity can provide depth, it does not always translate into actionable insights for insurers and financial decision-makers. Instead, Athena uses machine learning to generate structured, probability-based outputs that are stable and useful over time, enabling insurers, mortgage lenders, and municipal bond investors to confidently assess and price wildfire risk.
Probabilities, Not Predictions
A key distinction in risk modeling is understanding that probabilistic systems do not predict specific events — they provide risk assessments that hold value across a portfolio of exposures. Only an arsonist can know where a wildfire ignition will occur with confidence. In the real world, ignition events are random, but their progression to catastrophic wildfires are not. However, progression to large wildfires IS based on pre-existing conditions, like landmines.
An investor using an index fund does not bet on individual stocks but rather on a consistent, long-term approach that balances risk. Similarly, insurers do not need to know exactly where and when a wildfire will start; they need reliable probabilities that can be applied consistently across many locations to make risk-based decisions.
By using the same parameters and methodology across all assessed locations, Athena ensures that its probability outputs are not just accurate in isolated cases but consistent across time and space — a crucial requirement for insurance modeling. Yet using the unique characteristics of the bioregion, as shown in historic wildfires, allows Athena to build the terroir of the wildfires into its output. Obviously, if outcomes and risk were measured differently in different places, insurance pricing becomes erratic and unreliable. Athena solves this problem by maintaining a stable risk classification system that delivers uniform probabilistic assessments.
The Role of Machine Learning in Consistency
Rather than adding complexity, Athena’s Voice of the Acre® algorithm is designed to make it easy for people to use the Earth’s existing data for decisions, based upon recognize stable patterns in wildfire risk across diverse landscapes. It processes thousands of data points within several miles of any given location, identifying the most relevant variables while filtering out noise. This approach ensures that probabilities are not just generated but are also comparable across different geographies, making them useful for underwriting, capital allocation, and financial planning.
As climate change alters wildfire risks over time, Athena’s models continuously update, ensuring that probability assessments remain valid without losing consistency. This is key for insurers, who require a dependable framework for pricing risk year after year, even as environmental conditions shift.
Applying Consistent Risk Data to Insurance and Investment Portfolios
For insurers, municipal bond investors, mortgage and real estate portfolio holders, risk consistency is just as important as risk accuracy. Athena enables these stakeholders to:
- Price insurance policies with confidence by applying uniform risk assessments across large portfolios.
- Evaluate changes in risk over time without altering the underlying methodology, allowing for fair and transparent rate adjustments.
- Support risk-linked financial instruments, such as catastrophe bonds and municipal bonds, with stable risk data that enables more precise financial modeling.
For utilities and local governments, Athena’s consistent probability assessments provide clarity in prioritizing wildfire mitigation projects. Rather than reacting to the most dramatic fire risks, organizations can focus resources on areas where mitigation efforts will have the greatest financial impact — which is not always where fire risk is highest but where economic exposure is most significant.
In wildfire risk assessment, complexity is a challenge which prevents many of the leading wildfire models from offering stable, usable pre-ignition outcomes. Athena Intelligence does not attempt to solve the physics of wildfire. Its focus is commercially viable wildfire risk probabilities for the upcoming 12 months that can be used for mitigation decisions and risk pricing by insurers, investors, and financial professionals.
In a world where risk assessment can often feel uncertain, Athena provides what matters most: a stable foundation for decision-making.
Athena Intelligence is a data vendor with a geospatial, conditional, profiling tool that pulls together vast amounts of disaggregated wildfire and environmental data to generate spatial intelligence, resulting in a digital fingerprint of wildfire risk.
Clients include electric utilities, communities and financial services companies, where Athena’s geospatial intelligence incorporated into multiple products that can be accessed through an online portal. Athena’s data is currently used in wildfire mitigation plans (WMP) and public safety power shutoffs (PSPS), Community Wildfire Protection Plans (CWPP), property insurance underwriting and portfolio risk optimization.
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