Viewpoint: Is it Time to Rethink the ‘Secondary-Peril’ Label and Reclassify Risk?

August 12, 2026 by Vikas Wadhera

As climate events intensify, exposure is expanding, and loss severities from secondary perils, such as convective storms, wildfires, floods and hail, are no longer easily dwarfed by hurricanes or earthquakes. These perils have contributed significantly to the insured losses in the last few years, accounting for the substantial portion of the industry’s financial burden.

Hence, traditional “secondary” perils tag may no longer fit within that frame, given their growing role in risk models, pricing, capacity, and treaty design.

Secondary, Primary, or Something Else Entirely?

Historically, where the primary peril defined the catastrophe boundary, secondary perils lived inside it, contributing to tail losses more sporadically and with less certainty. But the lines between primary and secondary perils are blurring.

In some geographies, the annual loss burden from severe convective storms (SCS) or floods can now rival or surpass that of hurricanes. In others, wildfires burn across multiple seasons, shaping portfolio performance long after the primary event has passed. As such, the industry’s portfolios are becoming increasingly multi-hazard by design, even if the taxonomy hasn’t kept pace.

What’s Driving the Shift?

First, climate variability: Warmer, more volatile weather patterns are driving more intense convective storms, longer wildfire seasons, and more persistent flood events.

“Modeling firms are actively working to update catastrophe models to reflect this broadened risk spectrum. The core idea is to move from peril-centric modeling toward a more integrated, multi-peril framework.”

Second, exposure is growing: More properties are located in fire-prone or flood-prone regions, denser business districts, and infrastructure that was not designed to cope.

And third, the interplay among perils: A single event can trigger multiple perils (such as heavy rainfall leading to flooding and landslides), producing additional, interrelated loss profiles.

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Modeling the New Multi-Peril Landscape

Modeling firms are actively working to update catastrophe models to reflect this broadened risk spectrum. The core idea is to move from peril-centric modeling toward a more integrated, multi-peril framework that can capture:

Multi-peril dependencies: Covering how perils co-occur and interact, including tail dependencies where joint extreme outcomes can become more probable.

Climate-informed scenario sets: Incorporating forward-looking climate scenarios, not just historical weather data, to reflect potential shifts in severity and frequency.

Dynamic exposure and vulnerability: Accounting for growing exposure, urbanization, and changes in vulnerability (such as new construction methods or modified land use).

Data richness and validation: Leveraging satellite imagery, rainfall and fire data to refine calibration and governance.

“Boards and regulators increasingly demand transparency around correlations, tail risk, and the sensitivities of pricing to multi-peril dependencies.”

In practice, this means more complex, ensemble-style modeling. Insurers and reinsurers increasingly rely on multi-model outputs, cross-validated against portfolio-specific loss curves and industry loss data.

This shift also elevates the importance of model governance, model risk management, and the transparent communication of uncertainties to boards and regulators.

When done well, this allows pricing to reflect a portfolio’s true tail risk across a spectrum of hazards, not just a traditional hurricane-centric storyline.

Pricing, Capacity, and Treaty Architecture

If the risk picture has broadened, pricing must follow suit. The implications are threefold:

Premium realism: Pricing needs to reflect the full distribution of possible losses across all material perils – not just the expected losses but also, the tail risk, volatility, and the correlation between perils.

Capacity allocation and capital efficiency: Reinsurance capacity can be challenged when perils combine. The correlated losses across perils reduce diversification benefits and put pressure on the balance sheet capacity, limiting how efficiently reinsurers can deploy available capacity against compounding risk.

Treaty design that mirrors reality: Traditional, peril-specific treaties are giving way to structures that recognize the interdependencies across hazards. The goal is to align risk transfer with the true risk profile of a portfolio. Several features are now gaining traction:
- Peril-agnostic layers: Treaties that apply to a portfolio’s aggregate catastrophe risk, regardless of which peril triggers the loss. These layers sit atop a structure that can capture both primary shock events and secondary multi-peril events in a unified way.
- Multi-peril triggers and aggregate limits: Triggers calibrated to joint outcomes rather than a single peril. For example, one layer could kick in only when a combination of wind, rainfall, and fire weather severities crosses a given threshold, reflecting real-world damage drivers rather than a single-cat criterion.
- Index-based and parametric options: Parametric triggers tied to weather indices (rainfall depth, wind gust speeds, fire weather, etc.) offer rapid settlement and diversification benefits. While indemnity-based protection remains essential, parametric coverage can bridge the gaps left open by traditional triggers.
- Cross-peril retrocession and sidecars: Innovative structures can provide contingent capital precisely where multi-peril risk is most concentrated. These tools can improve balance-sheet resilience when models indicate elevated joint tail risk.
- Dynamic attach/take points and capital efficiency: Treaty terms may feature more dynamic banding, such as points that adjust with portfolio concentration, seasonality, or evolving exposure in high-risk geographies. This approach can keep capital aligned with actual risk.
A practical outcome is that pricing for a multi-peril portfolio becomes less about pricing per peril and more about pricing per realised risk, with explicit consideration of how perils interact.
This is where the risk-management dialogue with cedents, brokers, and capital partners becomes critical: shared governance over assumptions, data quality, and model validation is growing evermore fundamental to trust.
Governance, Transparency, and Regulator Dialogue
As models grow more sophisticated, governance must keep pace. Boards and regulators increasingly demand transparency around correlations, tail risk, and the sensitivities of pricing to multi-peril dependencies. This means:
- Clear documentation of assumptions: Why certain dependency structures were chosen, how climate scenarios were generated, and how exposure growth is factored into loss projections.
- Robust model risk management: Regular back-testing against industry losses, cross-model validation, and stress-testing that specifically probes joint-peril events.
- Communication with rating agencies and regulators: Explicit articulation of how treaty design reflects multi-peril realities, not traditional peril silos. This helps ensure that capital requirements and solvency assessments are aligned with actual risk geography and product mix.
The market response to a broader risk picture has been uneven but increasingly coherent. Some market participants have embraced integrated multi-peril frameworks responding to the evolving risk landscape, while others still operate within peril-specific playbooks.
The gap between the two camps is shrinking as clients demand more holistic coverage and capital partners insist on more rigorous, transparent modeling. In both cases, the trajectory is clear: credibility will come from the ability to quantify joint risk, manage model risk, and translate insights into structures that reflect how losses actually unfold when multiple perils collide.
Photograph: The Eaton Fire burns a residence on Wednesday, Jan. 8, 2025 in Altadena, Calif. (AP Photo/Ethan Swope, File)
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