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Impact Forecasting Launches First Fully Probabilistic Catastrophe Model For Flood In The Netherlands

Tool will enable the Dutch market to assess the flood risk and consider expanding insurance cover.

Impact Forecasting, has launched the first probabilistic catastrophe model to understand the financial impact of flood damage in the Netherlands for property and motor. Aon Benfield is the global reinsurance intermediary and capital advisor of Aon plc (NYSE:AON).

Flood, along with wind, is one of the most prevalent natural perils in the Netherlands, having experienced notable floods in 1953, 1993 and 1995. Losses from flood have traditionally been largely covered by the government but the private insurance market is now considering how it could support Dutch people and businesses. This means a catastrophe model is crucial to understand the nature of the hazard and its loss potential to enable adequate premiums to be charged for insurance and in turn for insurers to purchase the most effective reinsurance.

The model innovatively allows insurers to explore and better understand the extent of the damage for different hazard conditions, including:

  • Three different assumptions concerning the probability of flooding per dyke ring – an area with its own hydrological characteristics enclosed by a flood dyke – ranging from optimistic (less frequent) to pessimistic (more frequent)
  • Ability to assess effects of different motor evacuation patterns.

A co-operation with HKV, a Dutch research consultancy, and Deltares, an institute for applied research in the field of water, subsurface and infrastructure, means the model’s hazard and vulnerability components are enhanced through local knowledge on how flood risk is analysed, modelled and managed in the country.

Radek Solnicky, flood catastrophe model developer, commented: “Our dedicated flood team has ensured the model reflects the nuances of flood in the Netherlands to provide the most accurate insights for the insurance industry. This includes drilling down to look at residential, commercial and industrial properties potentially at risk, in addition to agricultural land. For example, the model also allows a greater understanding about the resilience to flood of different buildings including more unusual properties such as greenhouses.”

Adam Podlaha, head of Impact Forecasting, added: “This model is a landmark in catastrophe model development in how insurers can quantify uncertainty of different aspects of the hazard component. The new model enables insurers to obtain a clearer picture of how the financial impacts change if we consider optimistic, realistic or pessimistic probabilities of flooding. This will empower our clients to demonstrate to various stakeholders that they really own and understand the risk.”

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