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Helen YatesSeptember 06, 2019
RiskTropism
RiskTropism
Like Moths to the Flame
September 06, 2019

Why is it that, in many different situations and perils, people appear to want to relocate toward the risk? What is the role of the private insurance and reinsurance industry in curbing their clients’ risk tropism?  Florida showed rapid percentage growth in terms of exposure and number of policyholders If the Great Miami Hurricane of 1926 were to occur again today it would result in insurance losses approaching US$200 billion. Even adjusted for inflation, that is hundreds of times more than the US$100 million damage toll in 1926. Over the past 100 years, the Florida coast has developed exponentially, with wealthy individuals drawn to buying lavish coastal properties — and the accompanying wind and storm-surge risks. Since 2000, the number of people living in coastal areas of Florida increased by 4.2 million, or 27 percent, to 19.8 million in 2015, according to the U.S. Census Bureau. This is an example of unintended “risk tropism,” explains  Robert Muir-Wood, chief research officer at RMS. Just as the sunflower is a ‘heliotrope’, turning toward the sun, research has shown how humans have an innate drive to live near water, on a river or at the beach, often at increased risk of flood hazards.   “There is a very strong human desire to find the perfect primal location for your house. It is something that is built deeply into the human psyche,” Muir-Wood explains. “People want to live with the sound of the sea, or in the forest ‘close to nature,’ and they are drawn to these locations thinking about all the positives and amenity values, but not really understanding or evaluating the accompanying risk factors. “People will pay a lot to live right next to the ocean,” he adds. “It’s an incredibly powerful force and they will invest in doing that, so the price of land goes up by a factor of two or three times when you get close to the beach.”  Even when beachfront properties are wiped out in hurricane catastrophes, far from driving individuals away from a high-risk zone, research shows they simply “build back bigger,” says Muir-Wood. “The disaster can provide the opportunity to start again, and wealthier people move in and take the opportunity to rebuild grander houses. At least the new houses are more likely to be built to code, so maybe the reduction in vulnerability partly offsets the increased exposure at risk.” Risk tropism can also be found with the encroachment of high-value properties into the wildlands of California, leading to a big increase in wildfire insurance losses. Living close to trees can be good for mental health until those same trees bring a conflagration. Insurance losses due to wildfire exceeded US$10 billion in 2017 and have already breached US$12 billion for last year’s Camp, Hill and Woolsey Fires, according to the California Department of Insurance. It is not the number of fires that have increased, but the number of houses consumed by the fires.  “Insurance tends to stop working when you have levels of risk above one percent […] People are unprepared to pay for it” Robert Muir-Wood RMS Muir-Wood notes that the footprint of the 2017 Tubbs Fire, with claims reaching to nearly US$10 billion, was very similar to the area burned during the Hanley Fire of 1964. The principal difference in outcome is driven by how much housing has been developed in the path of the fire. “If a fire like that arrives twice in one hundred years to destroy your house, then the amount you are going to have to pay in insurance premium is going to be more than 2 percent of the value per year,” he says.  “People will think that’s unjustified and will resist it, but actually insurance tends to stop working when you have levels of risk cost above 1 percent of the property value, meaning, quite simply, that people are unprepared to pay for it.”   Risk tropism can also be found in the business sector, in the way that technology companies have clustered in Silicon Valley: a tectonic rift within a fast-moving tectonic plate boundary. The tectonics have created the San Francisco Bay and modulate the climate to bring natural air-conditioning. “Why is it that, around the world, the technology sector has picked locations  — including Silicon Valley, Seattle, Japan and Taiwan — that are on plate boundaries and are earthquake prone?” asks Muir-Wood. “There seems to be some ideal mix of mountains and water. The Bay Area is a very attractive environment, which has brought the best students to the universities and has helped companies attract some of the smartest people to come and live and work in Silicon Valley,” he continues. “But one day there will be a magnitude 7+ earthquake in the Bay Area that will bring incredible disruption, that will affect the technology firms themselves.” Insurance and reinsurance companies have an important role to play in informing and dissuading organizations and high net worth individuals from being drawn toward highly exposed locations; they can help by pricing the risk correctly and maintaining underwriting discipline. The difficulty comes when politics and insurance collide.  The growth of Fair Access to Insurance Requirements (FAIR) plans and beach plans, offering more affordable insurance in parts of the U.S. that are highly exposed to wind and quake perils, is one example of how this function is undermined. At its peak, the size of the residual market in hurricane-exposed states was US$885 billion, according to the Insurance Information Institute (III). It has steadily been reduced, partly as a result of the influx of non-traditional capacity from the ILS market and competitive pricing in the general reinsurance market.  However, in many cases the markets-of-last-resort remain some of the largest property insurers in coastal states. Between 2005 and 2009 (following Hurricanes Charley, Frances, Ivan and Jeanne in 2004), the plans in Mississippi, Texas and Florida showed rapid percentage growth in terms of exposure and number of policyholders. A factor fueling this growth, according to the III, was the rise in coastal properties.  As long as state-backed insurers are willing to subsidize the cost of cover for those choosing to locate in the riskiest locations, private (re)insurance will fail as an effective check on risk tropism, thinks Muir-Wood. “In California there are quite a few properties that have not been able to get standard fire insurance,” he observes. “But there are state or government-backed schemes available, and they are being used by people whose wildfire risk is considered to be too high.”

Helen YatesMay 20, 2019
catastrophes
catastrophes
Living in a World of Constant Catastrophes
May 20, 2019

(Re)insurance companies are waking up to the reality that we are in a riskier world and the prospect of ‘constant catastrophes’ has arrived, with climate change a significant driver In his hotly anticipated annual letter to shareholders in February 2019, Warren Buffett, the CEO of Berkshire Hathaway and acclaimed “Oracle of Omaha,” warned about the prospect of “The Big One” — a major hurricane, earthquake or cyberattack that he predicted would “dwarf Hurricanes Katrina and Michael.” He warned that “when such a mega-catastrophe strikes, we will get our share of the losses and they will be big — very big.” The use of new technology, data and analytics will help us prepare for unpredicted ‘black swan’ events and minimize the catastrophic losses Mohsen Rahnama RMS The question insurance and reinsurance companies need to ask themselves is whether they are prepared for the potential of an intense U.S. landfalling hurricane, a Tōhoku-size earthquake event and a major cyber incident if these types of combined losses hit their portfolio each and every year, says Mohsen Rahnama, chief risk modeling officer at RMS. “We are living in a world of constant catastrophes,” he says. “The risk is changing, and carriers need to make an educated decision about managing the risk. “So how are (re)insurers going to respond to that? The broader perspective should be on managing and diversifying the risk in order to balance your portfolio and survive major claims each year,” he continues. “Technology, data and models can help balance a complex global portfolio across all perils while also finding the areas of opportunity.” A Barrage of Weather Extremes How often, for instance, should insurers and reinsurers expect an extreme weather loss year like 2017 or 2018? The combined insurance losses from natural disasters in 2017 and 2018 according to Swiss Re sigma were US$219 billion, which is the highest-ever total over a two-year period. Hurricanes Harvey, Irma and Maria delivered the costliest hurricane loss for one hurricane season in 2017. Contributing to the total annual insurance loss in 2018 was a combination of natural hazard extremes, including Hurricanes Michael and Florence, Typhoons Jebi, Trami and Mangkhut, as well as heatwaves, droughts, wildfires, floods and convective storms. While it is no surprise that weather extremes like hurricanes and floods occur every year, (re)insurers must remain diligent about how such risks are changing with respect to their unique portfolios. Looking at the trend in U.S. insured losses from 1980–2018, the data clearly shows losses are increasing every year, with climate-related losses being the primary drivers of loss, especially in the last four decades (even allowing for the fact that the completeness of the loss data over the years has improved). Measuring Climate Change With many non-life insurers and reinsurers feeling bombarded by the aggregate losses hitting their portfolios each year, insurance and reinsurance companies have started looking more closely at the impact that climate change is having on their books of business, as the costs associated with weather-related disasters increase. The ability to quantify the impact of climate change risk has improved considerably, both at a macro level and through attribution research, which considers the impact of climate change on the likelihood of individual events. The application of this research will help (re)insurers reserve appropriately and gain more insight as they build diversified books of business. Take Hurricane Harvey as an example. Two independent attribution studies agree that the anthropogenic warming of Earth’s atmosphere made a substantial difference to the storm’s record-breaking rainfall, which inundated Houston, Texas, in August 2017, leading to unprecedented flooding. In a warmer climate, such storms may hold more water volume and move more slowly, both of which lead to heavier rainfall accumulations over land. Attribution studies can also be used to predict the impact of climate change on the return-period of such an event, explains Pete Dailey, vice president of model development at RMS. “You can look at a catastrophic event, like Hurricane Harvey, and estimate its likelihood of recurring from either a hazard or loss point of view. For example, we might estimate that an event like Harvey would recur on average say once every 250 years, but in today’s climate, given the influence of climate change on tropical precipitation and slower moving storms, its likelihood has increased to say a 1-in-100-year event,” he explains. We can observe an incremental rise in sea level annually — it’s something that is happening right in front of our eyes Pete Dailey RMS “This would mean the annual probability of a storm like Harvey recurring has increased more than twofold from 0.4 percent to 1 percent, which to an insurer can have a dramatic effect on their risk management strategy.” Climate change studies can help carriers understand its impact on the frequency and severity of various perils and throw light on correlations between perils and/or regions, explains Dailey. “For a global (re)insurance company with a book of business spanning diverse perils and regions, they want to get a handle on the overall effect of climate change, but they must also pay close attention to the potential impact on correlated events. “For instance, consider the well-known correlation between the hurricane season in the North Atlantic and North Pacific,” he continues. “Active Atlantic seasons are associated with quieter Pacific seasons and vice versa. So, as climate change affects an individual peril, is it also having an impact on activity levels for another peril? Maybe in the same direction or in the opposite direction?” Understanding these “teleconnections” is just as important to an insurer as the more direct relationship of climate to hurricane activity in general, thinks Dailey. “Even though it’s hard to attribute the impact of climate change to a particular location, if we look at the impact on a large book of business, that’s actually easier to do in a scientifically credible way,” he adds. “We can quantify that and put uncertainty around that quantification, thus allowing our clients to develop a robust and objective view of those factors as a part of a holistic risk management approach.” Of course, the influence of climate change is easier to understand and measure for some perils than others. “For example, we can observe an incremental rise in sea level annually — it’s something that is happening right in front of our eyes,” says Dailey. “So, sea-level rise is very tangible in that we can observe the change year over year. And we can also quantify how the rise of sea levels is accelerating over time and then combine that with our hurricane model, measuring the impact of sea-level rise on the risk of coastal storm surge, for instance.” Each peril has a unique risk signature with respect to climate change, explains Dailey. “When it comes to a peril like severe convective storms — tornadoes and hail storms for instance — they are so localized that it’s difficult to attribute climate change to the future likelihood of such an event. But for wildfire risk, there’s high correlation with climate change because the fuel for wildfires is dry vegetation, which in turn is highly influenced by the precipitation cycle.” Satellite data from 1993 through to the present shows there is an upward trend in the rate of sea-level rise, for instance, with the current rate of change averaging about 3.2 millimeters per year. Sea-level rise, combined with increasing exposures at risk near the coastline, means that storm surge losses are likely to increase as sea levels rise more quickly. “In 2010, we estimated the amount of exposure within 1 meter above the sea level, which was US$1 trillion, including power plants, ports, airports and so forth,” says Rahnama. “Ten years later, the exact same exposure was US$2 trillion. This dramatic exposure change reflects the fact that every centimeter of sea-level rise is subjected to a US$2 billion loss due to coastal flooding and storm surge as a result of even small hurricanes. “And it’s not only the climate that is changing,” he adds. “It’s the fact that so much building is taking place along the high-risk coastline. As a result of that, we have created a built-up environment that is actually exposed to much of the risk.” Rahnama highlighted that because of an increase in the frequency and severity of events, it is essential to implement prevention measures by promoting mitigation credits to minimize the risk.  He says: “How can the market respond to the significant losses year after year. It is essential to think holistically to manage and transfer the risk to the insurance chain from primary to reinsurance, capital market, ILS, etc.,” he continues. “The art of risk management, lessons learned from past events and use of new technology, data and analytics will help to prepare for responding to unpredicted ‘black swan’ type of events and being able to survive and minimize the catastrophic losses.” Strategically, risk carriers need to understand the influence of climate change whether they are global reinsurers or local primary insurers, particularly as they seek to grow their business and plan for the future. Mergers and acquisitions and/or organic growth into new regions and perils will require an understanding of the risks they are taking on and how these perils might evolve in the future. There is potential for catastrophe models to be used on both sides of the balance sheet as the influence of climate change grows. Dailey points out that many insurance and reinsurance companies invest heavily in real estate assets. “You still need to account for the risk of climate change on the portfolio, whether you’re insuring properties or whether you actually own them, there’s no real difference.” In fact, asset managers are more inclined to a longer-term view of risk when real estate is part of a long-term investment strategy. Here, climate change is becoming a critical part of that strategy. “What we have found is that often the team that handles asset management within a (re)insurance company is an entirely different team to the one that handles catastrophe modeling,” he continues. “But the same modeling tools that we develop at RMS can be applied to both of these problems of managing risk at the enterprise level. “In some cases, a primary insurer may have a one-to-three-year plan, while a major reinsurer may have a five-to-10-year view because they’re looking at a longer risk horizon,” he adds. “Every time I go to speak to a client — whether it be about our U.S. Inland Flood HD Model or our North America Hurricane Models — the question of climate change inevitably comes up. So, it’s become apparent this is no longer an academic question, it’s actually playing into critical business decisions on a daily basis.” Preparing for a Low-carbon Economy Regulation also has an important role in pushing both (re)insurers and large corporates to map and report on the likely impact of climate change on their business, as well as explain what steps they have taken to become more resilient. In the U.K., the Prudential Regulation Authority (PRA) and Bank of England have set out their expectations regarding firms’ approaches to managing the financial risks from climate change.  Meanwhile, a survey carried out by the PRA found that 70 percent of U.K. banks recognize the risk climate change poses to their business. Among their concerns are the immediate physical risks to their business models — such as the exposure to mortgages on properties at risk of flood and exposure to countries likely to be impacted by increasing weather extremes. Many have also started to assess how the transition to a low-carbon economy will impact their business models and, in many cases, their investment and growth strategy. “Financial policymakers will not drive the transition to a low-carbon economy, but we will expect our regulated firms to anticipate and manage the risks associated with that transition,” said Bank of England Governor Mark Carney, in a statement.   The transition to a low-carbon economy is a reality that (re)insurance industry players will need to prepare for, with the impact already being felt in some markets. In Australia, for instance, there is pressure on financial institutions to withdraw their support from major coal projects. In the aftermath of the Townsville floods in February 2019 and widespread drought across Queensland, there have been renewed calls to boycott plans for Australia’s largest thermal coal mine. To date, 10 of the world’s largest (re)insurers have stated they will not provide property or construction cover for the US$15.5 billion Carmichael mine and rail project. And in its “Mining Risk Review 2018,” broker Willis Towers Watson warned that finding insurance for coal “is likely to become increasingly challenging — especially if North American insurers begin to follow the European lead.” 

Helen YatesMay 11, 2018
Assigning a Return Period
Assigning a Return Period
Assigning a Return Period to 2017
May 11, 2018

Hurricanes Harvey, Irma and Maria (HIM) tore through the Caribbean and U.S. in 2017, resulting in insured losses over US$80 billion. Twelve years after Hurricanes Katrina, Rita and Wilma (KRW), EXPOSURE asks if the (re)insurance industry was better prepared for its next ‘terrible trio’ and what lessons can be learned  In one sense, 2017 was a typical loss year for the insurance industry in that the majority of losses stemmed from the “peak zone” of U.S. hurricanes. However, not since the 2004-05 season had the U.S. witnessed so many landfalling hurricanes. It was the second most costly hurricane season on record for the (re)insurance industry, when losses in 2005 are adjusted for inflation. According to Aon Benfield, HIM caused total losses over US$220 billion and insured losses over US$80 billion — huge sums in the context of global catastrophe losses for the year of US$344 billion and insured losses of US$134 billion. Overall, weather-related catastrophe losses exceeded 0.4 percent of global GDP in 2017 (based on data from Aon Benfield, Munich Re and the World Bank), the second highest figure since 1990. In that period, only 2005 saw a higher relative catastrophe loss at around 0.5 percent of GDP. But, it seems, (re)insurers were much better prepared to absorb major losses this time around. Much has changed in the 12 years since Hurricane Katrina breached the levees in New Orleans. Catastrophe modeling as a profession has evolved into exposure management, models and underlying data have improved and there is a much greater appreciation of model uncertainty and assumptions, explains Alan Godfrey, head of exposure management at Asta. “Even post-2005 people would still see an event occurring, go to the models and pull out a single event ID … then tell all and sundry this is what we’re going to lose. And that’s an enormous misinterpretation of how the models are supposed to be used. In 2017, people demonstrated a much greater maturity and used the models to advise their own loss estimates, and not the other way around.” It also helped that the industry was extremely well-capitalized moving into 2017. After a decade of operating through a low interest rate and increasingly competitive environment, (re)insurers had taken a highly disciplined approach to capital management. Gone are the days where a major event sparked a series of run-offs. While some (re)insurers have reported higher losses than others, all have emerged intact. “In 2017 the industry has performed incredibly well from an operational point of view,” says Godfrey. “There have obviously been challenges from large losses and recovering capital, but those are almost outside of exposure management.” According to Aon Benfield, global reinsurance capacity grew by 80 percent between 1990 and 2017 (to US$605 billion), against global GDP growth of around 24 percent. The influx of capacity from the capital markets into U.S. property catastrophe reinsurance has also brought about change and innovation, offering new instruments such as catastrophe bonds for transferring extreme risks. Harvey broke all U.S. records for tropical cyclone-driven rainfall with observed cumulative rainfall of 51 inches Much of this growth in non-traditional capacity has been facilitated by better data and more sophisticated analytics, along with a healthy appetite for insurance risk from pension funds and other institutional investors. For insurance-linked securities (ILS), the 2017 North Atlantic hurricane season, Mexico’s earthquakes and California’s wildfires were their first big test. “Some thought that once we had a significant year that capital would leave the market,” says John Huff, president and chief executive of the Association of Bermuda Insurers and Reinsurance (ABIR). “And we didn’t see that. “In January 2018 we saw that capital being reloaded,” he continues. “There is abundant capital in all parts of the reinsurance market. Deploying that capital with a reasonable rate of return is, of course, the objective.” Huff thinks the industry performed extremely well in 2017 in spite of the severity of the losses and a few surprises. “I’ve even heard of reinsurers that were ready with claim payments on lower layers before the storm even hit. The modeling and ability to track the weather is getting more sophisticated. We saw some shifting of the storms — Irma was the best example — but reinsurers were tracking that in real time in order to be able to respond.” The Buffalo Bayou River floods a park in Houston after the arrival of Hurricane Harvey How Harvey Inundated Houston One lesson the industry has learned over three decades of modeling is that models are approximations of reality. Each event has its own unique characteristics, some of which fall outside of what is anticipated by the models. The widespread inland flooding that occurred after Hurricane Harvey made landfall on the Texas coastline is an important illustration of this, explains Huff. Even so, he adds, it continued a theme, with flood losses being a major driver of U.S. catastrophe claims for several years now. “What we’re seeing is flood events becoming the No. 1 natural disaster in the U.S. for people who never thought they were at risk of flood.” Harvey broke all U.S. records for tropical cyclone-driven rainfall with observed cumulative rainfall of 51 inches (129 centimeters). The extreme rainfall generated by Harvey and the unprecedented inland flooding across southeastern Texas and parts of southern Louisiana was unusual. However, nobody was overly surprised by the fact that losses from Harvey were largely driven by water versus wind. Prior events with significant storm surge-induced flooding, including Hurricane Katrina and 2012’s Superstorm Sandy, had helped to prepare (re)insurers, exposure managers and modelers for this eventuality. “The events themselves were very large but they were well within uncertainty ranges and not disproportionate to expectations,” says Godfrey. “Harvey is a new data point — and we don’t have that many — so the scientists will look at it and know that any new data point will lead to tweaks,” he continues. “If anything, it will make people spend a bit more time on their calibration for the non-modeled elements of hurricane losses, and some may conclude that big changes are needed to their own adjustments.” But, he adds: “Nobody is surprised by the fact that flooding post-hurricane causes loss. We know that now. It’s more a case of tweaking and calibrating, which we will be doing for the rest of our lives.” Flood Modeling Hurricane Harvey also underscored the importance of the investment in sophisticated, probabilistic flood models. RMS ran its U.S. Inland Flood HD Model in real time to estimate expected flood losses. “When Hurricane Harvey happened, we had already simulated losses of that magnitude in our flood model, even before the event occurred,” says Dr. Pete Dailey, vice president of product management and responsible for U.S. flood modeling at RMS. “The value of the model is to be able to anticipate extreme tail events well before they occur, so that insurance companies can be prepared in advance for the kind of risk they’re taking on and what potential claims volume they may have after a major event,” he adds. Does this mean that a US$100 billion-plus loss year like 2017 is now a 1-in-6-year event? Harvey has already offered a wealth of new data that will be fed into the flood model. The emergency shutdown of the Houston metropolitan area prevented RMS meteorologists and engineers from accessing the scene in the immediate aftermath, explains Dailey. However, once on the ground they gathered as much information as they could, observing and recording what had actually happened to affected properties. “We go to individual properties to assess the damage visually, record the latitude and longitude of the property, the street address, the construction, occupancy and the number of stories,” he says. “We will also make an estimate of the age of the property. Those basic parameters allow us to go back and take a look at what the model would have predicted in terms of damage and loss, as compared to what we observed.” The fact that insured losses emanating from the flooding were only a fraction of the total economic losses is an inevitable discussion point. The majority of claims paid were for commercial properties, with residential properties falling under the remit of the National Flood Insurance Program (NFIP). Many residential homes were uninsured, however, explains ABIR’s Huff. “The NFIP covers just the smallest amount of people — there are only five million policies — and yet you see a substantial event like Harvey which is largely uninsured because (re)insurance companies only cover commercial flood in the U.S.,” he says. “After Harvey you’ll see a realization that the private market is very well-equipped to get back into the private flood business, and there’s a national dialogue going on now.” Is 2017 the New Normal? One question being asked in the aftermath of the 2017 hurricane season is: What is the return period for a loss year like 2017? RMS estimates that, in terms of U.S. and Caribbean industry insured wind, storm surge and flood losses, the 2017 hurricane season corresponds to a return period between 15 and 30 years. However, losses on the scale of 2017 occur more frequently when considering global perils. Adjusted for inflation, it is seven years since the industry paid out a similar level of catastrophe claims — US$110 billion on the Tohoku earthquake and tsunami, Thai floods and New Zealand earthquake in 2011. Six years prior to that, KRW cost the industry in excess of US$75 billion (well over US$100 billion in today’s money). So, does this mean that a US$100 billion-plus (or equivalent in inflation-adjusted terms) loss year like 2017 is now a one-in-six-year event? As wealth and insurance penetration grows in developing parts of the world, will we begin to see more loss years like 2011, where catastrophe claims are not necessarily driven by the U.S. or Japan peak zones? “Increased insurance penetration does mean that on the whole losses will increase, but hopefully this is proportional to the premiums and capital that we are getting in,” says Asta’s Godfray. “The important thing is understanding correlations and how diversification actually works and making sure that is applied within business models. “In the past, people were able to get away with focusing on the world in a relatively binary fashion,” he continues. “The more people move toward diversified books of business, which is excellent for efficient use of capital, the more important it becomes to understand the correlations between different regions.” “You could imagine in the future, a (re)insurer making a mistake with a very sophisticated set of catastrophe and actuarial models,” he adds. “They may perfectly take into account all of the non-modeled elements but get the correlations between them all wrong, ending up with another year like 2011 where the losses across the globe are evenly split, affecting them far more than their models had predicted.” As macro trends including population growth, increasing wealth, climate change and urbanization influence likely losses from natural catastrophes, could this mean a shorter return period for years like last year, where industry losses exceeded US$134 billion? “When we look at the average value of properties along the U.S. coastline — the Gulf Coast and East Coast — there’s a noticeable trend of increasing value at risk,” says Dailey. “That is because people are building in places that are at risk of wind damage from hurricanes and coastal flooding. And these properties are of a higher value because they are more complex, have a larger square footage and have more stories. Which all leads to a higher total insured value. “The second trend that we see would be from climate change whereby the storms that produce damage along the coastline may be increasing in frequency and intensity,” he continues. “That’s a more difficult question to get a handle on but there’s a building consensus that while the frequency of hurricane landfalls may not necessarily be increasing, those that do make landfall are increasing in intensity.” Lloyd’s chief executive Inga Beale has stated her concerns about the impact of climate change, following the market’s £4.5 billion catastrophe claims bill for 2017. “That’s a significant number, more than double 2016; we’re seeing the impact of climate change to a certain extent, particularly on these weather losses, with the rising sea level that impacts and increases the amount of loss,” she said in an interview with Bloomberg. While a warming climate is expected to have significant implications for the level of losses arising from storms and other severe weather events, it is not yet clear exactly how this will manifest, according to Tom Sabbatelli, senior product manager at RMS. “We know the waters have risen several centimeters in the last couple of decades and we can use catastrophe models to quantify what sort of impact that has on coastal flooding, but it’s also unclear what that necessarily means for tropical cyclone strength. “The oceans may be warming, but there’s still an ongoing debate about how that translates into cyclone intensity, and that’s been going on for a long time,” he continues. “The reason for that is we just don’t know until we have the benefit of hindsight. We haven’t had a number of major hurricanes in the last few years, so does that mean that the current climate is quiet in the Atlantic? Is 2017 an anomaly or are we going back to more regular severe activity? It’s not until you’re ten or 20 years down the line and you look back that you know for sure.”

NIGEL ALLENMay 10, 2018
In the Eye of the Storm
In the Eye of the Storm
In the Eye of the Storm
May 10, 2018

Advances in data capture are helping to give (re)insurers an unparalleled insight into weather-related activity Weather-related data is now available on a much more localized level than ever before. Rapidly expanding weather station networks are capturing terabytes of data across multiple weather-related variables on an almost real-time basis, creating a “ground-truth” clarity multiple times sharper than that available only a few years ago. In fact, so hyperlocalized has this data become that it is now possible to capture weather information “down to a city street corner in some cases,” according to Earth Networks’ chief meteorologist Mark Hoekzema. “The greater the resolution of the data, the more accurate the damage verification” Mark Hoekzema earth networks This ground-level data is vital to the insurance industry given the potential for significant variations in sustained damage levels from one side of the street to the other during weather-related events, he adds. “Baseball-sized hail can fall on one side of the street while just a block over there might be only pea-sized hail and no damage. Tornados and lightning can decimate a neighborhood and leave a house untouched on the same street. The greater the resolution of the data, the more accurate the damage verification.” High-Resolution Perils This granularity of data is needed to fuel the high-resolution modeling capabilities that have become available over the last five to ten years. “With the continued increase in computational power,” Hoekzema explains, “the ability to run models at very high resolutions has become commonplace. Very high-resolution inputs are needed for these models to get the most out of the computations.” In July 2017, RMS teamed up with Earth Networks, capitalizing on its vast network of stations across North America and the Caribbean and reams of both current and historical data to feed into RMS HWind tropical cyclone wind field data products. “Through our linkup with Earth Networks, RMS has access to data from over 6,000 proprietary weather stations across the Americas and Caribbean, particularly across the U.S.,” explains Jeff Waters, senior product manager of model product management at RMS. “That means we can ingest data on multiple meteorological variables in almost real time: wind speed, wind direction and sea level pressure. “By integrating this ground-level data from Earth Networks into the HWind framework, we can generate a much more comprehensive, objective and accurate view of a tropical cyclone’s wind field as it progresses and evolves throughout the Atlantic Basin.” Another key advantage of the specific data the firm provides is that many of the stations are situated in highly built-up areas. “This helps us get a much more accurate depiction of wind speeds and hazards in areas where there are significant amounts of exposure,” Waters points out. According to Hoekzema, this data helps RMS gain a much more defined picture of how tropical cyclone events are evolving. “Earth Networks has thousands of unique observation points that are available to RMS for their proprietary analysis. The network provides unique locations along the U.S. coasts and across the Caribbean. These locations are live observation points, so data can be ingested at high temporal resolutions.” Across the Network Earth Networks operates the world’s largest weather network, with more than 12,000 neighborhood-level sensors installed at locations such as schools, businesses and government buildings. “Our stations are positioned on sturdy structures and able to withstand the worst weather a hurricane can deliver,” explains Hoekzema. Being positioned at such sites also means that the stations benefit from more reliable power sources and can capitalize on high-speed Internet connectivity to ensure the flow of data is maintained during extreme events. In September 2017, an Earth Networks weather station located at the Naples Airport in Florida was the source for one of the highest-recorded wind gusts from Hurricane Irma, registering 131 miles per hour. “The station operated through the entire storm,” he adds. “Through our linkup with Earth Networks … we can ingest data on multiple meteorological variables in almost real time” Jeff waters RMS This network of stations collates a colossal amount of data, with Earth Networks processing some 25 terabytes of data relating to over 25 weather variables on a daily basis, with information refreshed every few minutes. “The weather stations record many data elements,” he says, “including temperature, wind speed, wind gust, wind direction, humidity, dew point and many others. Because the stations are sending data in real time, Earth Networks stations also send very reliable rate information — or how the values are changing in real time. Real-time rate information provides valuable data on how a storm is developing and moving and what extreme changes could be happening on the ground.” Looking Further Ahead For RMS, such pinpoint data is not only helping ensure a continuous data feed during major tropical cyclone events but will also contribute to efforts to enhance the quality of insights delivered prior to landfall. “We’re currently working on the forecasting component of our HWind product suite,” says Waters. “Harnessing this hyperlocal data alongside weather forecast models will help us gain a more accurate picture of possible track and intensity scenarios leading up to landfall, and allow users to quantify the potential impacts to their book of business should some of these scenarios pan out.” RMS is also looking at the possibility of capitalizing on Earth Networks’ data for other perils, including flooding and wildfire, with the company set to release its North America Wildfire HD Models in the fall. For Earth Networks, the firm is capitalizing on new technologies to expand its data reach. “Weather data is being captured by autonomous vehicles such as self-driving cars and drones,” explains Hoekzema. “More and more sensors are going to be sampling areas of the globe and levels of the atmosphere that have never been measured,” he concludes. “As a broader variety of data is made available, AI-based models will be used to drive a broader array of decisions within weather-influenced industries.”

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