Canadian earthquake could cause half of losses in 100-year return period scenario

Catastrophe modeling firm AIR Worldwide estimates that the current 1.00% exceedance probability loss (or the 100-year return period loss) is approximately $231.5 billion and the long-term average annual loss from natural catastrophes and terrorism is $72.6 billion.

That’s compared with $219.4 billion for the 100-year return period in 2013, and $205.9 billion in 2011. All figures are in U.S. dollars.

The firm’s 2014 report is based on its global loss metrics on perils and regions its currently models, including most new models and updates released during the year, as well as updated industry exposure databases as of the end of 2013.

Related: Updated earthquake model for Canada released by AIR Worldwide

The report also includes two global insured loss scenarios close to the 100-year return period to show the variety of perils and regions that can combine to produces losses at a given EP level.

In one scenario, earthquake losses make up 77% of global insured losses of $228.9 billion, while flooding in Europe would make up 27% of losses.

“A single North America earthquake – an M6.7 earthquake that strikes just 7 miles outside downtown Montreal and damages properties in parts of Ontario and Quebec provinces in Canada, as well as parts of New York and Vermont in the United States – accounts for $115.3 billion, fully 50% of the global insured loss total for all perils,” the report notes.

In the second aggregate scenario, a North America tropical cyclone (a Category 4 storm striking in Florida) would result in $189.2 billion in insured losses, or 80% of total losses.

“Companies operating on a world stage need to understand their risk across global exposures to ensure they have sufficient capital to survive years of very high loss,” Bill Churney, COO of AIR Worldwide noted in a statement.

“Understanding—owning—this risk requires knowing both the likelihood of high-loss years and the diversity of events that could produce such losses. This is the real value of having credible catastrophe models across multiple perils and regions that can be analyzed together seamlessly—to fully anticipate possible global outcomes, including future catastrophes and future years that will produce losses exceeding any historical amounts.”