Impact Forecasting, the catastrophe model development centre of excellence at Aon Benfield, is helping insurers and reinsurers prepare for current and future US hurricane seasons with its innovative storm surge model. Ahead of the one-year anniversary of Hurricane Sandy’s US landfall yesterday, the model has been updated with the latest data from Sandy that enables insurers and reinsurers to calculate loss estimates and gauge the financial impact of a storm surge reoccurrence.
Hurricane Sandy, the second-costliest hurricane in US history, had an overall insurance impact of roughly $30bn to both private insurers and the US government’s National Flood Insurance Program(NFIP).
Siamak Daneshvaran, Head of Research and Development at Impact Forecasting, comments “Sandy showed that storm surge losses can be the dominating cause of loss, as opposed to wind, during a large hurricane event. In the last several years we have calibrated our implemented version of SLOSH-along with our proprietary wind-field model-while utilizing data using tide gauges. Our validation on both a hazard and loss level shows that SLOSH is very efficient for a stochastic model and is also reasonably accurate for storm surge risk analysis.”
Impact Forecasting has incorporated the latest recorded data from Sandy given its enormous size– spanning more than 1,000 miles at its peak- and unique track to build upon its existing storm surge model.
Steve Jakubowski, president of Impact Forecasting, said: “Soon after Hurricane Katrina, Impact Forecasting began work to implement SLOSH technology into our storm surge model. The model’s performance with Hurricane Ike in 2008, and again with Hurricane Sandy in 2012, proved to be the most accurate and reliable in the modelling industry. It is now more important than ever to respond to these large events by researching, developing and implementing flood catastrophe models that can better analyze the hazard of hurricane coastal and inland riverine flooding. We have also been applying damage functions specifically for flood inundation, which allow insurers and reinsurers to better understand their flood risk.”
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