It started to rain across the south of England just before Christmas 2013, and it kept raining until, by the end of January 2014, the region had suffered its wettest winter in a century. Tens of thousands of people suffered power outages and hundreds of homes flooded.
Customers of London-based Aviva Insurance had been warned. Based on weather predictions and a digital mapping tool that determines flood risk on a property-by-property basis, Aviva had sent 20,000 e-mails to customers along the River Thames valley warning that they would be flooded and what they needed to do. The company’s loss adjusters followed up, knocking on some doors and warning residents to move out anything of high value.
The factors behind any weather pattern are complex, but a recent study of the storms of the winter of 2013-14 led by researchers at Oxford University found ties between the record-breaking rain and climate change. To Aviva it’s an affirmation of its focus on climate change—both as a factor in pricing its insurance and in driving the company’s own investments.
The insurance industry depends on its ability to analyze risks and the costs of dealing with them. Increasingly, climate change is one of the critical factors it examines.
As one might expect from a group of people who spend their time looking for things to worry about, insurers have been studying climate change for decades. Munich Re, one of the largest providers of insurance to other insurance companies, termed “reinsurance,” published a booklet on floods that highlighted the risk of global warming back in 1973.
Still, isolating climate change as a single factor in any given insurance policy is not yet possible, industry experts say.
Instead, insurance companies follow some basic rules. They don’t independently insure areas that are clearly headed for trouble. Today, low-lying island regions like the Pacific Island states and the nations of the Caribbean, as well as countries in Africa, have established insurance pools that could cover some part of rebuilding costs if they are hit by extreme weather, pools that are funded by governments and in some cases reinsurers.
Risks are reëvaluated frequently—generally insurance policies are priced annually—suitable for something as changeable as the weather. At Munich Re, new data from analyzing their own losses from natural catastrophes as well as data on extreme weather events is constantly fed into their risk models so the company can separate an isolated surprise from a long-term trend, says Peter Hoppe, who heads the company’s climate-change research. Some models have begun to be adjusted in light of long-term climate trends, says Hoppe. Losses from some types of severe storms in the U.S., for example, have clearly risen over the past 35 years even when the rising value of property is taken into account.
In recent years insurers have gotten better at spreading their risks. In the wake of Hurricane Andrew, a storm that caused $26.5 billion in damage in Florida and Louisiana in 1992, companies put a greater focus on diversifying their risks, moving away from, for example, insuring every house on certain blocks, a practice that had overwhelmed some insurers with claims following Andrew, says Robert P. Hartwig, president of the Insurance Information Institute.
Part of that effort has involved better modeling of disasters in order to understand the likelihood of such large storms and the cost of them. And as data storage and computational costs fell in the following decades, insurers built models that became more accurate. When the record hurricane year of 2004-05 arrived, bringing Katrina’s disastrous landing in New Orleans and massive insurance losses, no individual insurer was excessively exposed.
In Europe, insurers now assess and manage three types of risks: annual average loss, losses with a likelihood of occurring once in 20 years, and losses with a likelihood of occurring once in 200 years. It’s a model that global academic and government leaders have suggested as one that corporations broadly could use in assessing their exposure to climate risk.
Not too long ago, insurance companies priced property insurance risk by postal code, says Zelda Bentham, group head of sustainability at Aviva. But her company developed a digital flood map based on a topographical graph of the whole United Kingdom. “We could understand if there were two properties in the same postal code, that one was at the bottom of a hill at a river and another was at the top of the hill,” she says. Looking at intense rainfalls, they began to map, in increments as small as 1.5 meters, where water pooled after intense storms.
This relatively pinpoint location became one of 30 factors the company looks at when pricing a policy. It also generated the list of homeowners the company contacted when it saw the British floods coming.
This new data poisoning tool lets artists fight back against generative AI
The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models.
Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist
An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.
Data analytics reveal real business value
Sophisticated analytics tools mine insights from data, optimizing operational processes across the enterprise.
Driving companywide efficiencies with AI
Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.