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Climate For Change: How Data Can Manage Weather Risk

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It’s a bright warm day. People are walking around parks and green spaces without jackets and catching a few rays of the sun. Cafes and restaurants are putting tables out on the sidewalks so customers can enjoy al fresco dining. A reason for businesses to celebrate? Not if you’re a Utah ski resort at the start of the winter season.

With satellite imaging, weather forecasts have been getting more reliable, but weather reports can be wrong – just ask anyone who lived through the UK’s great storm of 1987, famously missed by official forecasters – and people and businesses can still fall victim to spells of unseasonal warmth, rainfall or cold.

Today, thanks to increasingly sophisticated digital data-gathering and analytical tools, meteorologists are beginning to be able to record and forecast the weather more accurately, and at granular levels. The science, however, is not precise. For example, in 2016, the Indian Meteorological Department predicted a drought while a private forecaster said there would be normal rainfall. A better understanding of weather allows companies and governments the opportunity to improve how they plan their projects and day-to-day operations.

In Depth

When bad weather makes the headlines, it’s usually the catastrophic events –hurricanes, floods and wildfires. These natural disasters devastate economies and communities, and involve high levels of investment to prepare for and recover from.

But unexpected changes in the weather bring their own challenges. Unseasonably hot or cold conditions can impact local communities and businesses – think for example, Dutch brewer Heineken credited favorable beer-drinking weather to a spike in sales in 2016 but, on the other hand, there has been many a rainy summer that has hit business for an outdoor restaurant.

Abnormal weather is estimated to have some kind of impact on at least 70 percent of businesses around the world (perhaps as high as 88 percent), and leads to an annual variation of economic output of as much as $485 billion a year in the U.S. alone ($557 billion in 2017 prices) – about 3.5 percent of the country’s overall economy. That’s the equivalent of Hurricane Harvey ­– which is on course to be the most expensive single natural disaster in U.S. history with estimated insured losses of around $200 billion – hitting twice in a year.

Sudden changes in the weather can affect different sectors in different ways:

Retail, food and agribusiness: A cold summer could affect consumer-facing retailers, such as those selling products geared towards good weather. British DIY chain B&Q suffered a 4.7 percent fall in sales, thanks to the U.K.’s unseasonably wet 2017 summer – after all, who wants to buy barbecues and lawn furniture when it’s raining all the time? Further down the supply chain, farmers could find the quality and quantity of their output adversely affected by rain, frost, sharp temperature changes, and wind conditions.

Construction: Severe weather, whether it’s rain, snow or wind, can close building sites, and is consequently a major challenge for construction projects. When a severe bout of winter weather hit Europe a few years ago, German construction output fell by 24 percent. While construction workers often have a contingency fund to cover weather delays, or arrangements with financing organizations, failure to understand exactly where and when bad weather will hit can cause costs to radiate throughout projects.

Energy: Consumption is highly dependent on the weather. For example, a particularly cold winter could cause a sudden spike in energy bills. In warmer climates, a heat-wave might put similar pressure on air conditioning units, also causing energy costs to rise. Temperature can affect energy consumption in other ways: For instance, hot weather has been found to decrease the efficiency of energy grids, and high winds can also damage renewable energy infrastructure like turbines, passing prices on to utility companies.

The Difference Data Makes

The use of data and analytics is transforming the way we understand and protect against this type of risk. Insurers have started to use big data in innovative new ways to create products to help companies ride out the unexpected weather conditions.

Research firm Aite Group reports that 79 percent of insurers believe data and analytics will significantly impact the needs of property and casualty customers. Big data analysis can help perform risk and concentration analysis and catastrophe modeling, allowing for those companies to then take steps to better plan things like project implementation, sales and product strategies, and helps them manage risk through insurance and hedging.

This data is getting increasingly detailed. Current technology allows companies and risk underwriters to understand local weather conditions down to 250m by 250m square (820ft by 820ft) areas.

This unprecedented level of insight is unlocking whole new ways of managing and planning for weather risk.

Time For Claimless Insurance?

One of the most interesting ways in which data is transforming the way that companies manage weather risk is through parametric insurance. This is a type of insurance that pays out when certain parameters – such as rainfall levels or temperature – are met, rather than when a claim is filed.

Typically, when a loss occurs, a company will quantify that loss and then submit a claim to their insurance carrier. Instead, when a predetermined set of conditions is met under a parametric insurance policy, financial instruments automatically pay out a predetermined sum to policyholders.

“By using weather data and analytics, we can look at what the temperature has done for as long as weather has been recorded, and then create products tailored according to that data,” explains Paul Ramiz, Account Executive and Product Leader for Weather Risk at Aon Benfield. “So, if the temperature drops below 25 or 20 or 15 or 10 degrees, someone with parametric insurance would then receive a payout.”

This is only possible thanks to the combination of sophisticated, real-time weather tracking, with decades of historical weather data. It could transform the way we think about risk hedging.

“What we can now use is these parametric covers and triggers, and the data that supports it to offer companies an alternative solution” says Ramiz. “You’re using parameters to set what the risk is. And you can use multiple triggers to say when the policy would pay out.”

Weather Data and Disaster Relief

Weather data and analytics is also finding uses outside insurance, such as in helping with more effective disaster relief.

Cambodia has historically suffered from extensive flooding, which has caused millions of dollars of damage and cost thousands of lives. Weather data was crossed with data on communities and populations to create a deep understanding of the extent of the risk posed by floodwaters.

“By adding population data into the tool alongside geographic and historic flood data, we created detailed risk assessments for vulnerable communities that enabled scenario planning and rapid decision-making for when floods occur,” explains Brad Weir, Head of Aon Benfield Analytics, Asia .

This combination of various, granular data sets allowed the right parties to make the best, most informed decisions when developing flood risk mitigation strategies. “Having a tool that is accessible and mobile makes all the difference to those who are actually deployed and trying to respond to the situation,” says Gisele Henriques, Resilient Livelihoods Adviser, CAFOD. “When you have a disaster you have to respond quickly, and having good data at hand can be a matter of life or death.”

Changing Risk Perceptions Based On Data

“A real driver of this innovation, the reason we’re passionate about it, is that data is really changing the way the companies view weather risk,” says Ramiz. “Most people, including business leaders, view weather as something that happens – something they may call a force majeure or an act of God. What we’re seeing is a use of  data in a way that takes historical events and helps better predict future patterns.”

Today, by using the right combinations of data and tools more effectively and faster, communities and businesses can be more resilient than ever before.

Talking Points

“Earlier springs might not seem like a big deal – and who among us doesn’t appreciate a balmy day or a break in dreary winter weather – it poses significant challenges for planning and managing important issues that affect our economy and our society.” – Jake Weltzin, Ecologist, United States Geological Survey

“While we anticipate states and municipalities will adopt mitigation strategies for these [weather] events, costs to employ them could also become an ongoing credit challenge. Our analysis of economic strength and diversity, access to liquidity and levers to raise additional revenue are also key to our assessment of climate risks, as is evaluating asset management and governance.” – Michael Wertz, Vice President, Moody’s

Further Reading