The property insurance industry spent decades building a fire department optimized for infernos. The problem is today's risk landscape looks more like a thousand small fires burning simultaneously across a wider geography — and the trucks can't get to all of them.

That's the structural reality of secondary climate perils. And it's why the property insurance market is under more pressure than most industry leaders are prepared to admit.

We designed for the wrong threat

Property insurance was purpose-built for catastrophic, episodic events — a named hurricane making landfall, a major earthquake along a fault line. The models were calibrated for them. The reinsurance towers were stacked for them. The capital buffers were sized for them.

Secondary perils — floods, wildfires, severe convective storms, heatwaves, drought, freeze events — weren't the focus. They were the rounding error.

The models the industry built for hurricanes aren't wrong about hurricanes. They're just not built for what's actually killing profitability today.

The aggregation problem traditional insurance ignores

Here's what makes secondary perils structurally different: individual events often fall below deductibles. A hailstorm in Kansas. A week of flooding in an inland county. A wildfire in a smaller regional market. Each one appears manageable. Together, they quietly hollow out an underwriting book.

Traditional property insurance treats each event as a discrete claim. But secondary perils don't operate that way. They accumulate — across geographies, across quarters, across a portfolio — creating attritional loss patterns that standard pricing models underweight.

The result is predictable: insurers who thought they were adequately reserved find themselves short. They reprice. They tighten underwriting criteria. They pull capacity from high-frequency markets. Reinsurers, watching the same trend from the other side, reassess aggregate exposure and raise their floors.

In California wildfire zones, in Florida's flood-prone interior counties, in Midwest hail corridors — this isn't a future scenario. It's what's happening now. The market is already contracting in precisely the regions that need it most, leaving businesses and households with fewer options at higher prices.

Why traditional frameworks can't catch up fast enough

The core issue isn't awareness. It's architecture.

Most carriers are underwriting from ZIP code-level data. They're running loss models licensed from the same small group of vendors. Their claims processes were engineered for low-frequency, high-severity events — meaning they're slow, manual, and expensive when they face the opposite.

You cannot price frequency-driven risk accurately with tools calibrated for severity-driven risk. The feedback loops are too slow. By the time the loss data is credible enough to reprice, the exposure has already shifted. And in a market where climate volatility is accelerating, that lag compounds.

Thenullprotection gap — currently estimated at $181 billion globally — is a direct symptom of this mismatch. It isn't that risk is uninsurable. It's that the current infrastructure can't price it profitably at the granularity and speed the threat demands.

What closing the gap actually requires

Two structural adjustments are non-negotiable.

First: Underwriting must operate at the property level, not the ZIP code. Secondary perils are hyperlocal. A flood event affects one block differently than the next. Wildfire risk varies dramatically within a single county. Aggregate pricing at the ZIP code level bakes in adverse selection and mispricing by design. Satellite imagery, IoT sensors, and climate data make property-level assessment a commercial reality today. The carriers who adopt it gain a structural pricing advantage. The ones who don't will continue underwriting blind.

Second: parametric structures need to become a standard tool in the coverage toolkit, not a specialty product. Parametric insurance pays automatically when predefined physical triggers are met — wind speed, flood gauge readings, soil moisture levels. There's no claims investigation. No weeks-long adjustment process. For secondary perils — where frequency is high, and certainty of occurrence matters more than severity estimation — parametric fills the coverage gaps traditional indemnity policies leave open. Every gap that goes unfilled is a business or household that absorbs the loss directly.

The next five years

If frequency-driven climate volatility continues on its current trajectory — and there's no credible forecast that suggests otherwise — the property insurance market will split in two.

Carriers who modernize their risk infrastructure will gain access to markets others have abandoned. Those markets are real, underserved, and growing. The protection gap represents solvable risk — for carriers with the infrastructure to price it accurately.

Carriers who don't modernize will continue chasing historical data in a forward-looking risk environment. They'll misprice, overpay reinsurance, and face mounting pressure in every market where they've quietly pulled back.

AI-native underwriting, parametric structures, and property-level data aren't futuristic ideas. They're the operational infrastructure that makes the math work in a world where the next "secondary" event isn't secondary at all.

The industry built an excellent alarm system for the threats of the last century. Building one for this century requires starting with different assumptions —
and significantly better data.

Siddhartha Jha is the founder and CEO of Arbol, an AI-native multi-line insurer underwriting property, catastrophe, agriculture, energy, and specialty risk across several states and multiple countries.

Opinions expressed here are the author's own.

(Lead image credit: Dede/Adobe Stock)

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