Convergence 2020 report
Modelling climate risk
There are numerous challenges around modelling catastrophes, affecting pricing and the ability to accurately predict events. A number of panels at Convergence 2020 addressed these issues, coming at them from a variety of perspectives. Bermuda:Re+ILS reports.
Large inflows of alternative capital could explain why the price of catastrophe insurance has not risen in line with insured losses, according to panellists at ILS Bermuda’s Convergence 2020.
Speaking on a panel titled “Insurance-linked Securities (ILS) & Climate Change: How Can the Industry Rise with the Tide?”, David Flandro, managing director of analytics at Hyperion X, noted the disconnect between re/insurance industry catastrophe losses and the cost of insurance. Nominal catastrophe losses have grown exponentially in the last 40 years, but the price of cover has fluctuated within a relatively narrow price channel, he said.
“Why is it cheaper to buy coastal wind protection now than it was in 2013?” Flandro asked.
“Climate change means historical data is a poor indicator of present risk.” Kerry Emanuel, Massachusetts Institute of Technology
Part of the answer, according to Lixin Zeng, managing partner at Integral ILS, could be the increasing prevalence of alternative capital. He argued inflows of alternative capital have increased efficiency and changed the supply and demand dynamics, preventing price rises.
Flandro agreed that alternative capital has had an impact on prices, with yield-hungry investors seeing better opportunities in ILS than in many other asset classes, but suggested this trend has now run its course. Further bouts of quantitative easing could prolong market distortions, he conceded.
Craig Tillman, president of natural hazards risk, portfolio management, risk mitigation at RenaissanceRe Risk Sciences, emphasised the differences between long-term and short-term views of risk, which also impact pricing decisions.
Much of the cat coverage being written offers short-term cover, noted Tillman. “We need a rational price for today’s risk, not one that looks 50 years out and is not relevant to today,” he said.
Peter Dailey, vice president at Risk Management Solutions, stressed that modellers are trying to balance the impact of climate change on mean risk levels as well as overall risk volatility.
“Changes in risk volatility may not be perceptible in average figures,” Dailey explained. “Climate change could even mean more ups and downs, or more quiet years, which is also very important to insurers.”
The efficacy of the climate models that underpin catastrophe reinsurance had already been the subject of discussion in previous panels. One panel of academics took it in turns to call on the re/insurance industry to move on from an old generation of models that, they said, are no longer fit for purpose.
Cat models that use historical inputs are based on “short and incomplete” data that would be misleading, even if it were comprehensive, because of the impact of climate change, said Kerry Emanuel, professor of atmospheric science at the Massachusetts Institute of Technology.
Climate data is reliable only since the 1970s, Emanuel said, with recorded data before then so inaccurate that it is of little use to actuaries. And even if models had a long and accurate dataset to draw on, climate change means historical data is a poor indicator of present risk, he added. He called on re/insurers to turn to physical models that calculate risk without using historical data.
Emanuel noted that three separate teams of researchers, working independently of each other, had calculated that Harris County in Texas, which had been struck by Hurricane Harvey, was three times more likely to flood now than it had been in the 1980s.
The general mispricing of risk is having profound social and political consequences. Failure to incorporate more accurate models is putting people’s lives at risk by encouraging them to live in areas that are susceptible to natural disasters, said Emanuel.
“The people killed by Hurricane Katrina died, arguably, because risk was underestimated,” he said.
“A 1 percent increase in the cost of home ownership could lead to a 20 percent fall in house prices.” Matthew Eby, First Street Foundation
However, incorporating more accurate models could devastate some house prices by increasing the cost of home ownership in areas that are identified as being at greater risk of flooding than previously acknowledged. A 1 percent increase in the cost of home ownership could lead to a 20 percent fall in house prices, noted Matthew Eby, founder and executive director at First Street Foundation.
Eby said his model, which is not based on historical data, showed there are many more US homes at risk of flooding than traditional historical models imply. The model indicates that 14.6 million properties are in a flood risk area, compared to the 8.7 million properties suggested by historical models. Within 30 years another two million properties will be at risk of flooding, he added.
Eby hit out at “quasi monopolistic” modelling companies and said the industry was in need of disruption from startups with a new approach.
“Existing modelling firms have no incentive to change the way they estimate risk,” he said.
Models become more inaccurate when looking at long tail risks, or low frequency, high severity, events, Emanuel added.
Ross Stein, chief executive officer and co-founder at Temblor.com and adjunct professor of geophysics at Stanford University, noted that although earthquakes are different from floods and hurricanes, in terms of not being a climate-related phenomenon, they suffer from similar shortcomings in the predictive models used by actuaries, he said.
Different countries use very different models, creating a lack of consistency in approach and making it impossible to use historical data for these rare occurrences across geographic regions, he said.
Stein noted that airlines had excellent safety records because airplanes have black boxes allowing for detailed analysis every time there is a problem.
“Only 1 percent of houses have seismometers,” he noted. “We should have a black box in every building.”
On another panel, Andrew Hughes, managing principal and Hiscox partner at Hiscox ILS, admitted some of these criticisms were fair, but stressed they did not seek to give a complete picture of risk. “Models are not the be-all-and-end-all, but they are not obsolete,” he said. “They are the baseline from which you work.”
“We should have a black box in every building.” Ross Stein, Temblor.com
Back on the climate change panel, Tillman admitted greater transparency in catastrophe models would be a good idea. It should be easier to adjust the assumptions underlying models to allow re/insurers to express their own views on risk, he said.
“We are very worried about the interaction between climate change and social inflation,” said Tillman. “The latter is not captured well by vendor models.”
Dailey welcomed the prospect of disruption from new catastrophe modelling companies but warned that established providers had to strike a difficult balance between innovating and delivering the consistency of data that re/insurers need.
“The re/insurance industry needs consistency in the pricing of risk,” he said.