How global insurance prices a world of rising disasters

Insurance works by spreading risk across a large pool of policyholders: the many pay premiums so that the few who suffer losses can be compensated. The mathematics of this pooling depend on losses being somewhat unpredictable and distributed, not concentrated and correlated. When a single event causes losses across thousands of policyholders simultaneously, or when the frequency of damaging events rises year after year in the same region, the mathematics of the pool stop working as designed. That is the dynamic now playing out in global insurance markets as climate-related events impose growing losses.

How the insurance and reinsurance system is structured

Most consumers deal with primary insurers: the companies that issue home, car, and business insurance policies. But primary insurers do not carry all the risk themselves. They transfer a portion of it to reinsurers, which are specialist companies that insure the insurers. The global reinsurance industry is concentrated among a handful of very large players, and the prices they charge primary insurers for reinsurance coverage flow through directly into the premiums consumers pay. When a catastrophic event, such as a major hurricane, earthquake, or flood season, generates large reinsurance claims, reinsurers raise their prices at the next renewal cycle.

This pricing signal travels around the world. A severe hurricane season in the United States can raise home insurance premiums in Australia, because the same global pool of reinsurance capital is being drawn on.

Why insurers are retreating from some markets

In parts of the United States, Australia, and Europe, primary insurers have been withdrawing coverage from areas they assess as uninsurable at any commercially viable price. This happens when modelled future losses in a location, based on updated climate and hazard data, exceed any premium that consumers could realistically pay. Coastal properties exposed to rising storm surge risk, bushfire-prone land, and flood-plain housing have all experienced insurer withdrawal in various markets. When private insurance is unavailable, households face the choice of going uninsured, accessing government-backed insurance pools of last resort, or relocating.

The modelling challenge

Insurance pricing relies on historical loss data to estimate future losses. In a stable climate, this works reasonably well. In a changing climate, historical data systematically underestimates future risk: the floods that were once considered once-in-a-century events occur more frequently, and the areas that were once considered safe are now periodically inundated. Updating catastrophe models to incorporate forward-looking climate projections is an active area of work for insurers, regulators, and reinsurers, but the uncertainty involved is substantial, and different model choices lead to different premium outcomes.

What it means for Australia

Australia is one of the most disaster-exposed insured property markets in the world. Cyclones, floods, and bushfires generate significant insured losses in most years, and the frequency of major events has increased. Northern Queensland, parts of coastal New South Wales, and bushfire-adjacent communities have experienced significant premium increases or outright withdrawal by some insurers. The affordability of home insurance is now a policy concern at state and federal level, with inquiries examining whether market-based insurance can continue to function as the mechanism for managing household disaster risk in high-exposure areas. For the broader economy, a large uninsured loss from a major disaster falls back on government through disaster recovery payments.

The bottom line

Global insurance is functioning as designed: it is repricing risk accurately as that risk rises. The difficult consequence is that accurate pricing makes insurance unaffordable or unavailable in places where it is most needed, and the social and economic costs of that gap are only beginning to be understood.

This article was compiled by AI and screened before publishing. See our editorial standards.