2 December 2015 Insurance

Aon Benfield subsidiary develops French flood model

Impact Forecasting, Aon Benfield’s catastrophe model development unit, has developed a French flood scenario model in conjunction with reinsurer SCOR to better understand and prepare for the potential cost of a flood impacting the country’s major cities.

Impact Forecasting said that since 1980, France has annually averaged more than $500 million in economic losses from flood, ranking the second-costliest peril after windstorm.

“Further, simulations from the model show that a reoccurrence of historical flood events, such as Paris in 1910 and Lyon as far back as 1856, might cause significant flood losses today,” said the firm.

The company said its new model quantifies losses for historical and hypothetical flood scenarios for the cities of Paris, Lyon and Toulouse to help SCOR and Aon Benfield clients enhance their view of catastrophe risk in these high exposure areas.

“The first step of this model development was collaboration between SCOR, Impact Forecasting and Aon Benfield’s Paris team. This unique combination of market expertise and access to exposure data for model calibration enabled a more accurate vulnerability component of the model,” said the company.

The model uses detailed data and analysis from historical records and recent studies to reflect current hydrological conditions and potential flood risks, according to the firm. Simulations of flood inundation were carried out using two-dimensional hydrodynamic modeling to create high quality flood maps, which were designed for portfolio modeling but can also provide insightful information for primary underwriting, said Impact Forcasting.

“The key component for success was the detailed discussions with SCOR throughout the model development process and the flexibility of our ELEMENTS loss calculation platform to incorporate critical elements such as the latest modeled flows, flood extent shapes and vulnerability functions,” said Petr Puncochar, head of flood model development at Impact Forecasting.

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