In the face of growing interest in climate change impacts, several big catastrophe modelers said they’ve heard from more clients interested in receiving climate-related data and they believe the field is on the cusp of a change in the way modeling is done.
“It’s kind of like we’re in a paradigm shift,” said Karen Clark, owner of Boston-based Karen Clark & Co., a specialist in catastrophe risk, modeling and risk management.
Call it the weird weather underway, or all the media attention the topic of climate change gets, but modelers like Clark are hearing more from clients interested in modeling for the potential impacts of climate change.
Clark said her clients want new tools to test the impact of potentially more frequent extreme weather events on their portfolios. Her firm recently rolled out an add-on to its RiskInsight product, an open, global platform for catastrophe risk management.
The add-on, or module as it’s referred to, is HazardMapper, which among its other features can examine an event like a hurricane and increase its severity to give an insurer or reinsurer an idea of how that will impact its portfolio.
Such a tool may prove useful for hurricanes in particular, where a great deal of client interest in variability lies, modelers say.
According to the National Oceanic and Atmospheric Administration, “anthropogenic warming by the end of the 21st century will likely cause hurricanes globally to be more intense on average by 2 to 11 percent.”
Besides helping clients figure out the potential impacts of more severe storms, which may or may not be driven by climate change, the module can be used other ways – such as creating events like a magnitude 9 earthquake on the San Andreas fault – and it is designed for use by clients in-house.
Therefore, Clark couldn’t say exactly how clients are using it, or if the majority of them are using it to model for the impacts of climate change.
“I would say that a goodly number are using it to test the sensitivity of their loss estimates to different assumptions,” she said, referring to her belief that many clients may be looking at the potential impacts of climate change on their portfolios.
“New paradigm” was also a phrase used by Tom Larsen, senior vice president and product architect at CoreLogic EQECAT.
“There is a greater recognition that we have to do more,” said Larsen, who has for some time been calling attention to the need for more progressive models to deal with a changing climate. “We’re in a place where the empirical models that we’re using to date…are not sufficient to help us understand what this risk is going forward.”
Requests to offer clients climate-related data in models hasn’t been overwhelming by any means, but Larsen did say “there is a lot more interest.”
That interest for the most part is limited, because property insurance contracts are renewed annually and long-term data on climate change is not useful – even taking into account insurers’ strategic horizons of two, five or 10 years on books of business, that’s a short time compared to the decades that will pass before climate change begins impacting exposed properties.
“In those kinds of timescales, there’s not a lot of change in there,” Larsen said. But, he added, there is enough of an anticipated change in the climate – added to the current abnormal weather patterns that regularly make the 5 O’clock news – to “cause a lot of anxiety and a lot of probing.”
That anxiety may be among the reasons that many in the field are now including conditional frequency models based on assumptions about ensuing weather patterns, such as the adoption of tools like Tail-Value-at-Risk measurement, which quantifies an expected value of loss outside a given probability level.
A TVaR measurement, Larsen explained, looks beyond the 100-year, and 200-year static catastrophe models, which don’t offer a complete picture of how bad can it be, giving insurance and reinsurance executives better answers to questions like “Am I steering my business prudently?”
Silicon Valley-based modeler Risk Management Solutions last year partnered on the Risky Business initiative, a year-long effort co-chaired by former New York Mayor Michael Bloomberg, former Treasury Secretary Henry Paulson, and Farallon Capital founder Tom Steyer, to quantify and publicize the economic risks the U.S. faces from the impacts of a changing climate.
For the initiative RMS provided an analysis of the impacts that climate change will likely have on coastal infrastructure and related assets. Risky Business issued a report late last year focused on the clearest and most economically significant risks: “Damage to coastal property and infrastructure from rising sea levels and increased storm surge, climate-driven changes in agricultural production and energy demand, and the impact of higher temperatures on labor productivity and public health.”
Paul Wilson, vice president of model development for RMS and leader of the firm’s North Atlantic hurricane modeling team, said clients are often asking the same question: “How much variability can we expect?”
“That’s a conversation RMS has very regularly with our clients,” Wilson said. “We need to think about to what degree climate change is impacting that variability, to what degree is climate change impacting that baseline around which we build our models.”
In response to these conversations, RMS will be incorporating more variability into more models in future, although it’s the overall concern over variability, and not necessarily climate change, that may be driving some of that interest, he added.
Wilson is getting increasingly sophisticated requests from RMS clients, who no longer view models as just a “black box that just spits out a number.”
Those clients want to “own their own view of the risk,” he said. “They want better numbers, but the volatility of extreme weather also has them more interested – hurricane activity, tornadoes, drought – it’s making the users dig in much deeper and they want more sophisticated models.”
Some of the interest may also be a result of pressure from regulators.
Insurance commissioners in several large states have for the past few years been requesting increased disclosures from insurers pertaining to their climate change exposure. And more recently, the National Association of Insurance Commissioners Climate Change and Global Warming Working Group has taken up topics like: “Review the enterprise risk management efforts by carriers and how they may be impacted by climate change and global warming.”
Jayanta Guin, executive vice president of AIR Worldwide, said the modeler’s clients are increasingly being asked by regulators and rating agencies to explain what they are doing to manage the risk.
“And, in turn, our clients are looking to us to keep them apprised of the current state of the science and to educate the regulators and rating agencies on what the catastrophe models currently capture,” Guin said.
It’s not like the modeling industry is running to catch up to climate change impacts. All modelers spoken with said that as models are updated they capture the most recent seasons of higher or lower activity, so any impact a warming climate has had to this point is reflected in those models.
“While clients would welcome more of these climate-conditioned models and investigations into extreme disaster scenarios, there is considerable uncertainty in establishing robust relationships between various climate signals and the frequency of occurrence of natural disasters,” Guin said.
However, it’s is an active area of research for AIR scientists, he added.
“There does seem to be wider consensus that climate variability may increase, but the current climate is already highly variable—witness the nine-year drought of Florida hurricane landfalls,” he said. “One thing is clear: we cannot identify climate change as the cause of any single event, whether it is the record snowfall and cold temperatures in Boston this winter, or Hurricane Sandy’s onslaught of the New Jersey coast in 2012.”
Clark believes that while it would be nice to have models that precisely predict how much losses an insurer may incur in any given year, such information isn’t likely to be available in our lifetimes.
“We may be able to get slightly better models,” she said. “In our lifetime the models are never going to be accurate, they’re never going to be giving precise answers.”
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