Swiss Re's 2022 nat cat estimates indicate worldwide coverage gap

Swiss Re Institute's annual report estimates that natural catastrophes caused a total of $115 billion of insured losses around the world in 2022, with economic losses totaling to an estimated $268 billion. Hurricane Ian was the single largest contributor with an estimated $50 to $65 billion in losses, and secondary perils resulted in a loss of $50 billion. Increased financial losses are on par with trends from the past decade, and as losses driven by extreme weather continue to grow in numbers, so too does the need for insurance. However, Swiss Re estimated that 45% of the total global economic losses was covered by reinsurers, suggesting that a large coverage gap exists and continues to grow with the demand for adequate coverage.  

Thomas Holzheu, chief economist for the Americas of Swiss Re, says that this widening gap exists for a number of complicated reasons that vary by specific regions and perils; issues like risk perception, product design and affordability contribute greatly to the protection gap. 

For emerging economies, Holzheu says, "It's a question of affordability, and it's also a question of… familiarity with insurance products, financial literacy, the development of institutions like a distribution network and products that are attractive for a large share of the low income population. The rapid urbanization of emerging economies is leaving the demand and the infrastructure of the insurance industry behind, and there's a 'catch-up' to do."

This year's estimates indicate a large coverage gap for mature economies, as well, for specific perils like floods and earthquakes. How we perceive these risks contribute greatly to this gap in coverage, according to Holzheu, as our perceptions of natural catastrophes often depend on the frequency and exposure of such events to our own areas.

"Risk is abstract…there's a lot of psychology that trips us in evaluating [risk] properly. So these risk perception issues are particularly an issue around the risks of earthquakes and inland flood areas," Holzheu explains. "You simply don't think about it, but then you have extreme flooding from rainfall... in areas and regions that are not generally considered to be at risk."

Similarly, the modeling capabilities of extreme weather events require frequency and exposure to allow scientists to observe trends and record significant data points that improve model accuracy. 

"Modeling is an evolving science," Holzheu states. "For some perils, we already know much better [of] what's happening, because they happen more frequently. Other perils are more scarce, in terms of observations… and events that don't often happen can simply have less data points to work with. And some models are simply terribly complicated to model."

For insurers, data points like dense population and strong economic development are "both driving the accumulation of building values, commercial and personal. And that's a big driver of exposure. So, identifying the right trends is quite critical. So you [must] combine this science model and the economic input, and be sure that as an industry that you have the current exposure properly assessed," Holzheu says.