Risk assessment is an essential part of insurance: it is what ensures companies are competitive and customers are well-served. But what happens when the risk of climate-related insurance claims becomes more difficult to assess?

In the past, climate was stable and relatively predictable, and historic patterns could be used to predict the future. This is no longer the case; according to Robert Muir-Wood, chief scientist of Risk Management Solutions, “A paradigm shift from historic to predictive risk assessment methods is necessary.”

Extreme Weather is Forcing Insurance Companies to Rethink Their Models

In the age of big data and immense computational resources, predictive climate modeling has become a possibility. Environment Canada’s Canadian Centre for Climate Modelling and Analysis publishes century-long forecasts of climate models, tracking everything from soil moisture to snow cover to temperature based on several different scenarios.

 

The animation above (courtesy of DMW Insurance) shows one such model, which predicts the temperature on Canada Day to the year 2100. This is a snapshot of one day of the year, so there is variation as one would expect, but one thing is clear: this model predicts Ontario is going to get much hotter, with occasional heat waves topping 40 degrees for most of the province.

Good models depend on good data. As the years pass and more and more data is collected, models should become more and more predictive. This will be crucial to an insurance industry that must accurately weight the risk of claims from severe weather for centuries to come.

Read more:

How the Insurance Industry Is Dealing With Climate Change – (Smithsonian Magazine)

Warming of the Oceans and Implications for the (Re)insurance Industry – (Geneva Association)

Data Source: Environment Canada: Canadian Centre for Climate Modelling and Analysis