Property insurers have always needed to watch out for large losses that shock their balance sheets. Historically, the insurance industry has considered catastrophes the largest threats. Today, however, property insurers face an existential threat from another source: skyrocketing losses caused by secondary perils. In fact, secondary perils—led by severe convective storms—have surpassed catastrophes as the leading cause of insured loss.
Severe convective storms (SCS) are localized events accompanied by lightning, thunder, strong wind gusts, intense rainfall, and, in some instances, hail. An analysis by Aon found that from 1990 to 2022, U.S. SCS losses increased at an annual rate of 8.9%.
A problem for insurers and policyholders
In 2023, severe convective storms caused $64 billion in insured losses, 85% of those originating in the U.S., according to Swiss Re. This volume of loss in the U.S. alone resulted in ratings downgrades for dozens of insurers, and four companies became insolvent. Swiss Re notes that the fastest-growing category of disaster is medium-severity events, or those causing $1 billion to $5 billion in insured losses. More SCS events are falling into this category.
Options for insurers facing large losses from secondary perils are few but consequential for policyholders. Those options are:
- Raise rates or deductibles, making coverage unaffordable for policyholders
- Exclude coverage, reducing protection for secondary perils
- Withdraw from markets where losses from secondary perils are heaviest
When secondary perils cause company insolvencies, policyholders can lose access to insurance coverage. That leads to serious economic consequences for individuals, businesses, and communities.
See also: Blind Spots in Catastrophe Modeling
Traditional reinsurance isn’t solving this problem
For catastrophe losses, insurers have a ready source of financial protection in reinsurance. Insurers already buy catastrophe reinsurance because they’re required to have it—but catastrophe reinsurance doesn’t cover the effects of the accumulation of losses associated with much more frequent secondary perils.
Traditional reinsurance is not solving the problem of secondary perils because it is generally not available for the aggregation of such losses. At one time, reinsurers offered aggregate cover but could not write it affordably within their risk appetite.
Another reason reinsurers have avoided covering secondary perils at scale is the limitation of catastrophe models. Cat models have evolved significantly since the early 1990s, and they work well for low-frequency, high-severity events—such as one-in-250-year and one-in-500-year events. These models have proven unsuitable for high-frequency, lower-severity events. Many secondary perils are one-in-five-year or one-in-10-year events.
Without reinsurance to spread the risk of secondary perils, insurers have had no real financial option, until now.
See also: Litigation Risks in 2024 and Beyond
A path forward to keeping property coverage available
The high loss frequency of sub-catastrophic events—that is, lower- to medium-severity secondary perils—makes traditional risk transfer solutions untenable. At the same time, paying steady volumes of high-frequency, lower-severity losses is unsustainable. For these reasons, a new approach to reinsuring secondary perils is needed.
One such solution is parametric reinsurance. Parametric risk transfer is a useful tool that is becoming more common for primary insurance risks, from personal travel to crop damage. The mechanics of parametric coverage are relatively simple: Based on defined parameters that can be reliably measured (examples include flight delays or cancellations, or a certain level of rainfall or hail in a defined period), an agreed amount of coverage is triggered when those parameters are met. There is no need for loss adjustment and the additional costs that process entails. Parametric insurance benefits the buyer as well as the capital provider by providing certainty and efficiency in transferring risk.
Until recently, however, parametric solutions have not been used in the context of reinsurance. Parametric reinsurance uses sophisticated modeling to assess secondary peril risks, but not in the same way that catastrophe models do. Its model does not predict specific events. Instead, it uses firsthand claims data from an insurer and verified historical weather data to estimate the likelihood of aggregate losses in a given year for that insurer.
The parametric reinsurance solution’s trigger, therefore, is not a single event but an aggregate dollar amount of modeled losses. Parametric insurance models secondary peril losses on the specific weather ingredients that generated historical claims on covered properties. In this way, the parametric solution resembles excess-of-loss reinsurance. This scalable solution is available at different attachment points, subject to the protection needs and budget of the insurer. For example, if a property insurer has an expected aggregate SCS loss of $100 million, it can buy parametric coverage that attaches at a point that makes economic sense for the insurer.
This innovative solution fills a need that can keep insurance available for high-frequency, high-severity types of losses, on a portfolio basis.
