Empowering Reinsurance Companies with Advanced Algorithms Useable with ArcGIS
In the realm of wildfire risk assessment, reinsurance companies serve as the ultimate backstop for property reinsurance. The prosperity of this subsector within the insurance industry depends crucially on adeptly assessing and precisely pricing potential losses.
In essence, it involves synthesizing information about the regional terrain, historical fires, property-specific details, insights from fire science, and employing algorithms to transform this data into actionable information compatible with ESRI’s ArcGIS system. This platform is widely adopted, utilized by an estimated 90% of reinsurance companies.
This essay explores the transformative potential inherent in advanced algorithms leveraging extensive environmental datasets to formulate granular wildfire risk probabilities applicable in pricing property risk. Specifically, it delves into the conditional, geospatial, artificial intelligence risk assessment model presently deployed by Athena Intelligence, featuring individual profiles for every property across eight western states. The resulting output from this model is accessible for utilization within the ArcGIS environment, facilitating effective portfolio risk management.
The crux of Athena’s algorithm, Voice of the Acre®, lies in its adeptness at prioritizing the relevance of numerous factors pertaining to terrain data, climate data, and research into the nature and behavior of wildfires. While a substantial portion of this information is derived from natural sources, some aspects also reflect human activities. This wealth of data is then transformed into indexes, derivatives, and calibrated scores, ultimately yielding precise profiles that reflect computable probabilities. This outcome serves as a strategic tool for reinsurance companies, facilitating the effective pricing of wildfire risk.
By harnessing the capabilities of advanced algorithms to create profiles based on probabilities, rather than merely describing or indexing conditions, reinsurance companies can make more informed decisions. This enables them to optimize syndication, insurance-linked securities (ILS), or other capital funding tools for a more effective risk management strategy.
Comprehending the local history of wildfire incidents is pivotal when assessing various tools. For instance, the May 2022 fire in Laguna Niguel serves as a pertinent case for evaluation.
Coastal Fire Destroys Homes in Socal's Laguna Niguel
At least 20 homes were burned in Laguna Niguel after a brush fire spread through the southern California city.
A commonly used model, utilizing an index of risk factors, identified the neighborhood as high risk. In contrast, another prominent “artificial intelligence” wildfire risk model, widely utilized, portrayed the neighborhood as low risk, resulting in losses for property insurers and reinsurers.
The actual situation was more nuanced. Similar to many wildfires, the Laguna Niguel fire from May 11 to 17, 2022, initiated in an uninhabited area and progressed into the Wildland Urban Interface (WUI). The Wildland Urban Interface represents the zone where inhabited areas are closely situated to uninhabited regions. The wildfire’s footprint looked like this:
The analysis of the same area, provided by Athena’s Voice of the Acre® algorithm several months before the fire, is shown numerically and geospatially.
The data, presented in the form of a polygon from Athena, can seamlessly be imported into ArcGIS. Users familiar with ESRI’s platform recognize that, despite ArcGIS’s constraints in prioritizing relevance or computing probabilities, it remains widely used and valuable for integrating historical data, including images, into a comprehensive spatial analysis. When coupled with Athena’s Voice of the Acre®, reinsurers can leverage ArcGIS to gain a nuanced understanding of past wildfire patterns, vegetation changes, and environmental factors. This, in turn, contributes to the formulation of more accurate and comprehensive risk assessments.
The synergy of combining the output of a superior probabilistic algorithm with ArcGIS empowers reinsurance companies to strategically allocate capital to areas with the highest returns within the realm of wildfire risk. In other words, it facilitates investment in regions where the compensation aligns accurately with the risk, instilling confidence. The precise identification of probabilities by property, grounded in terrain, climate, and local history, equips reinsurers with the strategic capability to price risk effectively, thereby mitigating potential earnings losses.
Athena Intelligence is an InsurTech 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.
For power companies, this helps them assess, a year in advance, where a consequential fire is most likely. For insurance or financial services companies, this assists in underwriting, portfolio risk optimization and loss cost probabilities for reserving.
Contact us at info@Project-Athena.com and follow us here.