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Helen YatesMay 11, 2018
Hurricane Claims
Hurricane Claims
Bringing Clarity to Slab Claims
May 11, 2018

How will a new collaboration between a major Texas insurer, RMS, Accenture and Texas Tech University provide the ability to determine with accuracy the source of slab claim loss? The litigation surrounding “slab claims” in the U.S. in the aftermath of a major hurricane has long been an issue within the insurance industry. When nothing is left of a coastal property but the concrete slab on which it was built, how do claims handlers determine whether the damage was predominantly caused by water or wind? The decision that many insurers take can spark protracted litigation, as was the case following Hurricane Ike, a powerful storm that caused widespread damage across the state after it made landfall over Galveston in September 2008. The storm had a very large footprint for a Category 2 hurricane, with sustained wind speeds of 110 mph and a 22-foot storm surge. Five years on, litigation surrounding how slab claim damage had been wrought rumbled on in the courts. Recognizing the extent of the issue, major coastal insurers knew they needed to improve their methodologies. It sparked a new collaboration between RMS, a major Texas insurer, Accenture and Texas Tech University (TTU). And from this year, the insurer will be able to utilize RMS data, hurricane modeling methodologies, and software analyses to track the likelihood of slab claims before a tropical cyclone makes landfall and document the post-landfall wind, storm surge and wave impacts over time. The approach will help determine the source of the property damage with greater accuracy and clarity, reducing the need for litigation post-loss, thus improving the overall claims experience for both the policyholder and insurer. To provide super accurate wind field data, RMS has signed a contract with TTU to expand a network of mobile meteorological stations that are ultimately positioned in areas predicted to experience landfall during a real-time event. “Our contract is focused on Texas, but they could also be deployed anywhere in the southern and eastern U.S.,” says Michael Young, senior director of product management at RMS. “The rapidly deployable weather stations collect peak and mean wind speed characteristics and transmit via the cell network the wind speeds for inclusion into our tropical cyclone data set. This is in addition to a wide range of other data sources, which this year includes 5,000 new data stations from our partner Earth Networks.” The storm surge component of this project utilizes the same hydrodynamic storm surge model methodologies embedded within the RMS North Atlantic Hurricane Models to develop an accurate view of the timing, extent and severity of storm surge and wave-driven hazards post-landfall. Similar to the wind field modeling process, this approach will also be informed by ground-truth terrain and observational data, such as high-resolution bathymetry data, tide and stream gauge sensors and high-water marks. “The whole purpose of our involvement in this project is to help the insurer get those insights into what’s causing the damage,” adds Jeff Waters, senior product manager at RMS. “The first eight hours of the time series at a particular location might involve mostly damaging surge, followed by eight hours of damaging wind and surge. So, we’ll know, for instance, that a lot of that damage that occurred in the first eight hours was probably caused by surge. It’s a very exciting and pretty unique project to be part of.”

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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