When assessing risk, how do you calculate premiums with precision? What makes an insurance assessment any better than guesswork? After all, when Florida’s most destructive hurricane to date struck the state in 1992, guesswork is often all that it was.
Before Hurricane Andrew stripped homes to their concrete foundations, killed dozens of people and bankrupted 11 insurance firms, catastrophe modeling was not taken seriously. Models were forecasting potential hurricane damage in the order of eight or nine times more severe than assessors would believe.
But emerging insurance losses of $15.5 billion months later proved that modeling made within hours of Andrew’s landfall was 85% accurate, forecasting almost double the presumed worst-case scenario of $7 billion. It was newly apparent to the industry: catastrophe modeling works.
In Australia, an independent research and development company called Risk Frontiers was formed in response to this new acknowledgement. Using modeling to solve and understand complex, practical problems, it advises the insurance sector on the best approaches to risk.
“For insurers to manage their risk, minimise losses and accurately price policies,” says Risk Frontiers chief geospatial scientist Dr James O’Brien, “knowing the exact location of a building or house, in relation to hazards such as flood or bushfire, is imperative.”
Quality data is what makes catastrophe modeling work. Modeling is only as good as the data that goes into it. As any junior programmer will tell you: garbage in, garbage out.
To provide that exact data, the company uses a product from location data experts Pitney Bowes called GeoVision.
“Risk Frontiers uses GeoVision data such as building footprints, tree height, and vegetation cover,” says Dr O’Brien, “to inform natural disaster models used by insurers which calculate risk and assess damage.”
In a flood, building heights can be analysed with GeoVision to know which properties are most at risk of flooding. In a bushfire, emergency services can use it to analyse tree density to see which properties are most threatened. Residents receive early warnings to protect themselves or to evacuate, and first responders are deployed where they’re needed most. This saves lives.
Governments can also respond with relief aid more effectively when local councils can provide accurate reports to state government on the number and type of buildings affected.
Insurance companies can set more realistic premiums on two similar properties on the same street if they know that one of the properties has a large tree capable of causing serious damage in a storm.
“GeoVision gives a much higher level of accuracy in data right across Australia than what’s ever been available before,” says Dr O’Brien. “Insurance companies, individuals, and emergency services have access to a whole lot of data that hasn’t been available in the past.”
Hurricane Andrew is no longer the costliest hurricane in the United States records or the most destructive to ever hit Florida; Katrina and Irma have since surpassed it. But its legacy is that risk can be calculated, and - with the right data - calculated with precision.