Is the world becoming uninsurable?

By Sebastien Argence

Back in 2024, Swiss Re warned that some areas were becoming “uninsurable,” after the industry significantly underestimated the impact of natural disasters across Europe. At the time, they pointed to events such as the Turkey earthquake, floods in Germany and hailstorms in Italy, where loss estimates were off not by 10% or 20%, but by entire factors. The problem, they said, was systemic: Their models were struggling, and the industry lacked up-to-date data on exposure and current risk values.

Two years in, those concerns haven’t faded. In conversations with insurers and reinsurers today, I hear the same urgency. Global insurance losses from natural catastrophes continue to grow at an annual rate of 5 to 7 percent, a trend that shows no sign of slowing. According to the Swiss Re Institute, 2025 marked the sixth consecutive year in which insured losses from natural catastrophes exceeded 100 billion US dollars.

As weather extremes intensify and asset values continue to rise, the gap between modeled risk and actual loss is only growing, and so are the questions around what still makes economic sense to insure. Naturally, the industry is looking for ways to build resilience into portfolios and reduce impact. That means improving prevention, reducing the workload when claim volumes surge, and rethinking how weather intelligence is used to structure products and price risk.

One of the key challenges remains the limitations of traditional weather models and services. Their spatial resolution is often too coarse to capture hyperlocal risks like hail or flash flooding. And even when data exists, it’s rarely delivered in a way that integrates cleanly into underwriting or claims workflows. That’s where there needs to be a shift in the industry.

Here are four ways insurance companies can adapt to the new risk realities via access to tailored weather intelligence:

Short-term success is reliant on long-standing historical insights.

Historical weather data is one of the most effective levers to quantify risk where it’s changing fastest. When certain regions experience a rising frequency of hailstorms or wind events, this evolution can be reflected more accurately in underwriting and pricing decisions. This kind of data helps insurers move from reacting after losses to adjusting portfolios ahead of them.

Warn policyholders before disaster strikes.

Prevention and early warning are seeing growing investment. I’ve been speaking with companies who now rely on high-resolution forecasting models to anticipate severe weather events hours or days in advance. With these timely forecasts insurers can warn policyholders, reducing claims and, in many cases, preventing millions in damage. It also builds trust. Even when losses still occur, the ability to give early warnings helps shift the insurer–client relationship from transactional to proactive.

Verify the validity of damage claims

Of course, not everything can be prevented. And when the worst happens, some will try to take advantage. For insurers, this means their focus must shift to verifying which claims are valid and which are money grabs.

Doing this, however, isn’t easy. Claims come in fast and heavy, and verifications can take days. In moments like that, having fast access to accurate weather data that shows what happened and where it happened can change everything. Tools on the market can streamline verification, from days to minutes, by making event evidence easier to access. This saves both money and time, especially when additional resources don’t have to be brought in just to cope with surges.

Prepare for long-term risk now

Looking further ahead, climate projections are becoming a key part of strategic planning. If a storm costs $5 million today, how much will that same type of storm cost in five years? $10 million? $20 million? Climate scenarios help estimate how risk distributions may shift over time and support portfolio stress testing.

These projections rest on the quality, resolution and accessibility of the data. Downscaled historical datasets offer the kind of spatial and temporal precision that makes a real difference across perils, especially hail, which has become a major concern as asset values and repair costs climb. With these insights integrated into existing workflows, underwriting, claims, portfolio analysis and more can all become more connected.

Demand for these capabilities is only going up. What used to be considered secondary perils are now front and center in boardroom discussions. And the financial consequences of extreme weather are increasingly hard to ignore. So the question is how well the sector can adapt its tools and processes.

The world may be moving toward a new threshold of insurability. But that doesn't mean insurers are powerless. On the contrary, there's a huge opportunity to rethink how they manage weather-driven risk. Those who succeed won’t eliminate it, but they’ll be in a much better position to keep portfolios healthy and continue playing the essential role insurance was built for.