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Insurance Solutions
Formerly Moody’s RMS
London, U.K. - January 16, 2018 RMS, a global risk modeling and analytics firm, has won a prestigious award for its new high-definition flood models for Europe, in recognition of their potential to transform risk management for the continent’s flood (re)insurers. The RMS Europe Inland Flood HD Models were awarded Best Catastrophe Risk Modeling Solution at the 2017 InsuranceERM Awards.
In the last two decades, flood has accounted for a third of all European natural catastrophe losses. But until now modelers were forced to use short-cut approximations because computers could not handle the complexity associated with applying flood risk science at high-resolution over the entire continent. Flood risk can differ significantly at properties only meters apart, while affecting huge regions of the continent across national boundaries. The new model is a major step forward for the industry, because it exploits the computational power of the cloud to represent flood risk, using the latest scientific evidence, at a highly granular level.
Commenting on the award, Dr. Maurizio Savina, a hydrologist and director of international flood model management at RMS said, “with Europe’s broad weather systems, coupled with the complicated transnational river networks, flood is very much a pan-European problem. So, we set out to create the first pan-European solution, spanning 13 countries, that could also model how floods change over hours and days using a continuous time and space simulation. It’s been a fantastic RMS team effort, very much a labour of love, and we’re delighted to see the end result receive this acclaim.”
The RMS model can be adopted for selected countries or as a pan-European set. It has recently proved its worth to numerous clients during 1/1 renewals, and many more are expected to have completed model validation in time for 2019 renewals. Flood Re, the UK not-for-profit scheme funded by insurers, is also using the RMS Europe Inland Flood HD Model in the United Kingdom
Further information about the capabilities of the RMS model can be found here.
