What the Los Angeles fires taught us about a catastrophe peril unlike any other

Author: Firas Saleh, Director - Product Management - Insurance, Moody's

The recent Palisades and Eaton fires in Los Angeles were a devastating reminder of wildfire's destructive power.

With insured loss estimates reaching $30 billion, these events have been catapulted into the most destructive wildfires in U.S. history. But beyond the staggering losses, these fires offer an opportunity—a masterclass in risk, to reveal that wildfire is a peril fundamentally different from other major catastrophes. Managing this risk effectively means moving beyond old analogies and embracing the unique, complex nature of this peril, including the rapidly evolving landscape of who and what is insured.

Insight 1: The anatomy of the LA Fires - A perfect storm

The LA fires were the result of a historically unique convergence of factors that created a "perfect storm":

1. Antecedent conditions: The region had experienced its third warmest and second driest period on record. This was preceded by two historically wet winters, which created an abundance of fine fuels (grass and brush) that were then perfectly dried out.

2. Historic winds: The Santa Ana winds that drove the fires were in the top two percent of highest recorded speeds for the area.

3. Suppression overload: Crucially, this wasn't just one fire. Multiple fires ignited across Southern California simultaneously. At the time of ignition, only nine fire engines were pre-deployed in the area, a fraction of the 40 or more that might have been staged for such conditions. High winds grounded helicopters, and resources from neighboring counties were busy fighting their blazes.

Insight 2: Boots on the ground: What on-site reconnaissance revealed

Three months after the Palisades and Eaton fires were contained, a team from Moody’s traveled to the impacted areas. The goal was to move beyond satellite imagery and data to get a ground-level view, to understand not just what burned, but why.

This on-site investigation yielded critical insights that were essential to validate the underlying assumptions of the Moody’s RMS™ U.S. Wildfire HD Model.

Here are the key takeaways:

1. The "shadow effect" of fire suppression: One of the most interesting observations was why some pockets of homes survived untouched amid widespread destruction. This was seen in several cases, such as a large, defensible structure like a school or a set of homes on a defensible ridgeline. This effort created a "shadow" downstream, shielding the houses behind it from the ember-driven, house-to-house spread that defines an urban conflagration. It’s a powerful demonstration that defending one key asset can save an entire neighborhood.

2. The critical role of urban firebreaks: The advance of the urban conflagration in Altadena was not random. Its westward spread was halted decisively by an unlikely feature: a large cemetery. The irrigated grass and lack of combustible structures from the Mountain View cemetery in Altadena created a natural firebreak, impassable for continued house-to-house fire spread.

This observation highlights how even in a dense urban grid, features like parks, golf courses, and wide boulevards can provide firefighters a critical advantage and serve as definitive boundaries for a fire's growth.

Figure 1: Google satellite image showing properties destroyed by fire to the west and north of the Mountain View cemetery in Altadena, compared to unaffected properties to the east of the cemetery.

3. House-level vulnerabilities drive ignition: In areas where one house was destroyed and its neighbor was not, the difference often came down to small details. Reconnaissance confirmed the importance of "ember accumulators"—architectural features like dormers, eaves, and corners where wind-blown embers can gather and ignite the structure.

It also highlighted the danger of "connected fuels." High building density, small lots, and flammable wooden fences or overgrown shrubbery that touch the house create a direct bridge for fire to travel from one property to the next, accelerating the conflagration.

4. Smoke damage is a major, hidden loss driver: Even in homes that were structurally sound and not directly touched by flame, the evidence of significant loss was clear. Streets were lined with discarded carpets, furniture, and mattresses—items that absorb the pervasive, acrid smoke.

This scene, more reminiscent of a flood cleanup, underscored that smoke damage is a major financial component of a wildfire event, often leading to tens of thousands of dollars in claims for a single, unburned property.

These on-the-ground observations are not just interesting anecdotes; they are crucial data points. They validate the Moody’s RMS model assumptions about suppression and provide real-world evidence for how phenomena like urban conflagration, ember transport, and secondary modifiers for mitigation work in practice, ensuring the model reflects the complex reality of a modern wildfire.

Insight 3: Wildfire loss vs. hurricanes

It has been common for the insurance industry to view catastrophes through the well-understood lens of hurricane risk. Yet, the LA fires underscore why this analogy doesn't fully capture the unique nature of wildfire, especially at the extreme, or "tail," end of the risk curve.

The divergence begins with the physical footprint. A major hurricane (e.g., Milton in 2024) can impact trillions of dollars of exposure across an entire state, whereas the devastating LA wildfires affected a combined exposure of around $35 billion to $40 billion.

As seen in Figure 2 below, this orders-of-magnitude difference in scale physically constrains the maximum loss potential of a single wildfire event.

This physical constraint has a profound impact on the financial nature of the risk. When viewing catastrophic losses as a multiple of the average annual loss (AAL), the hurricane tail is significantly steeper. A rare hurricane can produce a loss many times greater than its AAL due to the potential for widespread damage across a vast area. For wildfire, this multiple is much smaller (see Figure 3 below).

Ultimately, wildfire tail risk is not driven by a massive storm system but by a rare and complex phenomenon: urban conflagration. It behaves less like a hurricane and more like a high-category tornado—intensely destructive but geographically limited.

Insight 4: The evolving nature of exposure

A key challenge in modeling wildfire risk today is that the ground truth of what is insured is shifting dramatically. The industry can no longer assume that the economic value in a high-risk area directly translates to insured value.

Analysis shows a stark trend: in California's highest-risk wildfire zones, insurance take-up rates are declining. As private carriers pull back, homeowners are increasingly turning to the FAIR Plan, California's insurer of last resort. 

This matters for two reasons:

1. An increasing insurance gap: The number of non-renewals is highest precisely in the areas that drive the most wildfire loss. This creates a growing gap between the total economic value at risk and the actual insured value.

2. Underinsurance potential: FAIR Plan policies have historically had coverage limits that may not fully cover the reconstruction cost of properties in affluent, high-risk areas.

This dynamic means that the economic view of risk and the insured view of risk are diverging. A model must be calibrated to the economic reality to provide a stable, long-term view, while also being flexible enough to account for the current, complex insurance landscape.

Why is the Moody's RMS North America Wildfire HD Model critical?

The complexity revealed by the LA fires demonstrates why a new generation of wildfire models is no longer a luxury but a necessity.

The Moody's RMS U.S. Wildfire HD Model is designed to capture the specific nuances that drove this event:

1. Simulating urban conflagration: The model doesn't just examine where a fire might burn in the wildland; it explicitly simulates the leap to a dense urban environment—the house-to-house spread that defines an urban conflagration. By running over a million years of these specific simulations, the model can identify areas at higher risk for this rare but catastrophic outcome.

2. Quantifying the value of mitigation: The model includes advanced "secondary modifiers" to account for property-level hardening (e.g., non-combustible siding) and community-level mitigation (e.g., fuel treatment programs). These modifiers help insurers to quantify the real-world risk reduction of these efforts, empowering them to offer incentives and build more resilient communities.

The way forward

The Los Angeles wildfires were a painful lesson in the evolving nature of catastrophe. They proved that wildfire is a complex interplay of hazard, fuel, topography, and, critically, human intervention and market dynamics. To underwrite, price, and manage this risk, the industry needs tools built for this specific reality. By embracing the insights from these events and leveraging advanced models, insurers can move from simply reacting to losses to proactively building a more resilient future.