CoreLogic, a residential property information, analytics and data-enabled services provider, has released an expanded version of its natural catastrophe risk management program, which features a probabilistic flood model to analyze the potential damage and financial impact at the property-level from flood events in the continental United States.
According to the company, the probabilistic flood model is unique to the industry because its riverine and flash flood risk components provide better risk estimation for areas outside the 100-year flood zones—areas responsible for 20 percent of historic flood losses but which represent only 1 percent of the flood insurance policies in force.
Measuring both severity and frequency of flood events, the probabilistic flood model loss calculations offer property, contents and business interruption analysis. The model also incorporates historical flood event footprints from the last 50 years and the accompanying property damage. Additionally, the model incorporates detailed user-provided building information to derive vulnerability assessments driven by both water depth and water velocity. These building characteristics include construction type, occupancy, floor elevation, basements and elevated building configurations.
With granular 10-meter elevation data, the catastrophe risk management program also incorporates the Digital Flood Insurance Rate Maps (DFIRMs) provided by the Federal Emergency Management Association (FEMA). It uses more than 80 different occupancy classes covering topography, land-use, stream coverage and inundation. In order to more accurately measure a property’s flood risk, more than 50 data layers ranging from elevation, hydrologic and catchment information are included, as well as data for over 6 million miles of streams and 20,000 stream flow gauges.
“The release of the U.S. Inland Flood Model means insurers can now use this advanced probabilistic tool to help them determine a property’s potential for flood damage,” said Tom Larsen, CoreLogic product architect. “The model’s unique ability to provide granularity down to the property-level will offer insurers a complete view of flood risk, including contents and business interruption, for all types of properties.”
The catastrophe risk management program contains parcel-level geocoding through PxPoint from CoreLogic, which can convert physical addresses or locations into precise geographic coordinates for over 142 million parcel boundaries. A new visualization feature identifies details in the data as well as exceptions via easy-to-use charts and graphics. Other new components include updates to three risk assessment models including Italy Earthquake, the North Atlantic Hurricane Risk and U.S. Offshore Energy. Highlights include:
- The Italy Earthquake Model now incorporates an updated seismic source model based on the Seismic Hazard Harmonization in Europe (SHARE) to provide a current and more accurate view of seismic hazard in Italy. Increased maximum magnitudes, an updated magnitude-frequency distribution and a new ground motion model are part of the enhancements.
- The North Atlantic Hurricane Risk Model update includes a high-resolution storm surge model and enhanced hazard risk assessment to more accurately capture the damage from storm surge as the surge attenuates inland (outside of the high velocity zones). It uses storm intensities from historical events based on the Atlantic hurricane reanalysis project by the National Oceanic and Atmospheric Administration (NOAA). Additionally, the North Atlantic Hurricane Risk Model includes a full set of default secondary structural modifiers by vintage and location for all hurricane states, which are based on the International Building Code as well as state-specific building codes to provide refined results. RQE 16® also includes a model version which was certified by the Florida Commission Hurricane for Loss Projection Methodology in June 2015.
- The U.S. Offshore Energy Model features a distinctive wave model component and unique financial model which produces an improved estimate of potential damage to physical assets in U.S. territorial waters within the Gulf of Mexico. A network analysis is also built into the model to produce a better estimate of the lost production from oil wells.
“All of these enhancements will help insurers understand hazard risk in a more granular and comprehensive way, and this precision in risk modeling will help the industry overall fine-tune its underwriting, claims and reinsurance efforts,” said Larsen.
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