TigerRisk’s head of analytics Nathan Schwartz considers whether 2017 was an unusually busy year for catastrophes, or whether other factors simply made it seem more eventful than usual
What does it mean for a random outcome to be “unusual”?
We all have a sense that if the lottery came up with the numbers 01, 02, 03, 04, 05 and 06, then that would be fantastically unlikely. But at the same time, we all know that an orderly string of numbers is no more or less unlikely than the normal-looking 03, 11, 38, 44, 58 and 02 – the actual Powerball lottery outcome on 4 August 2018.
The US aggregate insured loss for 2017 had around a 20- or 30-year return period depending on how it is modelled. Most people would agree that it was more unusual than that. The question is why.
Was it because we’ve entered a new age of detailed media coverage? Or was there something different about the events of the year? Perhaps it was the mix of events? You don’t have to play with the numbers much to conclude that 2017 was unusual. It was. But was it unlikely?
There are at least three lenses through which we measure likelihood: size of events, number of events and characteristics of events.
According to industry loss estimates, US insured losses in 2017 were around $100bn – an unremarkable number on its own. But how those losses came about, in a parade of moderate to large events, was what made 2017 stand out.
