Going beyond historical data brings clarity to the future of wildfire risk
Welcome to the second installment of our four-part series on wildfire hazard and enterprise risk management where we will explore wildfire risk models from CoreLogic® and their optimal use within the insurance industry ecosystem. We recommend that you read part one prior to reading this piece. Watch for part three, which will be released in the coming weeks.
The Simulation-Based Approach: Enhancing Enterprise Risk Management
In the realm of wildfire risk assessment and models, there is debate on the utilization of historical data versus simulation-based approaches. Traditionally, proponents of historical data have touted its reliability and accuracy as a basis for assessing risks. However, the limitation of historical data lies in its inability to capture the full scope of potential future events, especially in the case of perils like wildfire.
Wildfires are inherently dynamic and are influenced by multifaceted factors beyond historical occurrences. Certain areas, previously untouched by fires, might be overlooked as low-risk zones if one depends solely on historical records.
Challenges of Historical Data: A Lesson From California’s Wildfires
Consider this scenario: if we constrained ourselves to historical data up until 2017, numerous areas would appear virtually risk-free. Take the California towns of Santa Rosa and Paradise as examples. Until 2017, these places had never witnessed a single recorded fire. However, the 2017 Tubbs Fire in Santa Rosa and the 2018 Camp Fire in Paradise destroyed 5,643 and 18,804 structures, respectively. Relying solely on historical data can lead to overlooking areas in California with the potential for wildfire.
Simulation Models for Forward-Looking Risk Assessment
In contrast, simulation-based models introduce a forward-looking perspective by simulating fires that have not yet occurred. This approach acknowledges the evolving nature of risks, allowing the inclusion of areas that may have a negligible historical risk but still possess the potential for high-severity burns in the future. This widens the spectrum of risk assessment for carriers while enabling better preparedness strategies for communities that could be at risk in the coming years.
Learn About 2023 Wildfire Risk
Redefining Urban Areas: The Importance of Edge Propagation in Wildfire Risk Modeling
A key differentiator in the CoreLogic model is its approach to urban areas. Unlike conventional models that rely on shifting existing perimeters, the CoreLogic approach involves redefining urban areas as a fuel type. This shift results in more realistic fire spread patterns, especially at the critical edges of the fire footprint where much of the wildfire damage occurs. Therefore, having an accurate representation of edge propagation is imperative for effective risk assessment and wildfire mitigation planning.
Beyond just the fire footprint, CoreLogic’s model also takes into account an often-overlooked aspect of wildfires — smoke. The inclusion of smoke modeling provides a distinct advantage, enabling financial terms to be attached to smoke-related impacts.
While historical data remains a critical piece of the puzzle, simulation models offer a forward-looking vantage point that enhances our understanding of risk. These models can identify potential high-risk areas that historical data might miss. Additionally, accurate edge propagation and smoke modeling gives a level of granularity that empowers stakeholders to more precisely tailor their risk management strategies by adjusting sublimits or incorporating smoke-specific considerations.
Empowering the Insurance Industry: CoreLogic’s Probabilistic Wildfire Model
The CoreLogic U.S. Wildfire Model can provide insurers and reinsurers with these insights at either the single property level or the portfolio level, empowering the industry to appropriately and rationally estimate risk to obtain better business outcomes. As a comprehensive probabilistic model, it simulates wildfire activity based on the hazard today to fully calculate the likelihood of a wildfire starting, spreading and damaging property.
Our U.S. Wildfire Model is powered by the same property and hazard data built into the Wildfire Risk Score, but it expands the analysis a step further. The Wildfire Risk Score quantifies the hazard at any given location within the model, while the Wildfire Model can estimate the loss and the likelihood of that loss occurring by simulating hundreds of thousands of annual wildfire scenarios.
In a world where risks are constantly evolving, adopting these tools is a logical step forward in creating more resilient and adaptive communities.
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