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To be Solvency II compliant, re/insurers must validate the models they use, which can include comparisons to historical loss experience. In working towards model validation, companies may find their experience of European windstorm hazard does not match the modeled loss. However, this seeming discrepancy does not necessarily mean something is wrong with the model or with the company’s loss data. The underlying timelines for each dataset may simply differ, which can have a significant influence for a variable peril like European windstorm.

Most re/insurers’ claims records only date back 10 to 20 years, whereas European windstorm models use much longer datasets – generally up to 50 years of the hazard. Looking over the short term, the last 15 years represented a relative lull in windstorm activity, particularly when compared to the more extreme events that occurred in the very active 1980s and 1990s.

european windstorm

RMS has updated its European windstorm model specifically to support Solvency II model validation. The enhanced RMS model includes the RMS reference view, which is based on the most up-to-date, long-term historical record, as well as a new shorter historical dataset that is based on the activity of the last 25 years.

By using the shorter-term view, re/insurers gain a deeper understanding of how historical variability can impact modeled losses. Re/insurers can also perform a like-for-like validation of the model against their loss experience, and develop confidence in the model’s core methodology and data. Alternate views of risk also support a deeper understanding of risk uncertainty, which enhances model validation and provides greater confidence in the models that are used for risk selection and portfolio management.

Beyond Solvency II validation, the model also empowers companies to explore the hazard variability, which is vitally important for a variable peril like European windstorm. If a catastrophe model and a company rely on different but equally valid assumptions, the model can present a different perspective to provide a more complete view of the risk.

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Many (re)insurers may be taken aback by the level of claims arising from floods in the French Riviera on October 3, 2015. The reason? A large proportion of the affected homes and businesses they insure in the area are nowhere near a river or floodplain, so many models failed to identify the possibility of their inundation by rainfall and flash floods. Effective flood modeling must begin with precipitation (rain/snowfall), since river-gauge-based modeling of inland flood risk lacks the ability to cope with extreme peaks of precipitation intensity. Further, a credible flood model must incorporate risk factors as well as the hazard: the nature of the ground, such as its saturation level due to antecedent conditions, and the extent of flood defenses. Failing to provide such critical factor can cause risk to be dramatically miscalculated. A not so sunny Côte d’Azur This was clearly apparent to the RMS event reconnaissance team who visited the affected areas of southern France immediately after the floods. “High-water marks for fluvial flooding from the rivers Brague and Riou de l’Argentiere were at levels over two meters, but flash floodwaters reached heights in excess of one meter in areas well away from the rivers and their floodplains,” reported the team. This caused significant damage to many more ground-floor properties than would have been expected, including structural damage to foundations and scouring caused by fast-floating debris. Damage to vehicles parked in underground carparks was extensive, as many filled with rainwater. Vehicles struck by more than 0.5 meters of water were written off, all as a result of an event that was not modeled by many insurers. The Nice floods show clearly how European flood modeling must be taken to a new level. It is essential that modelers capture the entire temporal precipitation process that leads to floods. Antecedent conditions—primarily the capacity of the soil to absorb water must be considered, since a little additional rainfall may trigger saturation, causing “saturation excess overland flow” (or runoff). This in turn can lead to losses such as those assessed by our event reconnaissance team in Nice. Our modeling team believes that to achieve this new level of understanding, models must be based on continuous hydrological simulations, with a fine time-step discretization; the models must simulate the intensity of rainfall over time and place, at a high level of granularity. We’ve been able to see that models that are not based on continuous precipitation modeling could miss up to 50% of losses that would occur off flood plains, leading to serious underestimation of technical pricing for primary and reinsurance contracts. What’s in a model? When building a flood model, starting from precipitation is fundamental to the reproduction, and therefore the modeling, of realistic spatial correlation patterns between river basins, cities, and other areas of concentrated risks, which are driven by positive relationships between precipitation fields. Such modeling of rainfall may also identify the potential for damage from fluvial events. But credible defenses must also be included in the model. The small, poorly defended river Brague burst its banks due to rainfall, demolishing small structures in the town of Biot. Only a rainfall-based model that considers established defenses can capture this type of damage. Simulated precipitation forms the foundation of RMS inland flood models, which enables representation of both fluvial and pluvial flood risk. Since flood losses are often driven by events outside major river flood plains, such an approach, coupled with an advanced defense model, is the only way to garner a satisfactory view of risk. Visits by our event reconnaissance teams further allow RMS to integrate the latest flood data into models, for example as point validation for hazard and vulnerability. Sluggish growth in European insurance markets presents a challenge for many (re)insurers. Broad underwriting of flood risk presents an opportunity, but demands appropriate modeling solutions. RMS flood products provide just that, by ensuring that the potential for significant loss is well understood, and managed appropriately.…

Laurent Marescot
Laurent Marescot
Senior Director, Model Product Strategy, RMS

Based in Zurich, Laurent initially joined RMS in 2008 as part of the Zurich account management team, servicing the European (re)insurance and ILS market. He then moved to the model product management group, leading the technical product management team for European climatic perils, such as windstorm, severe convective storm and flood. Since 2014, he has joined the model product strategy group for Europe model product line.

Prior to RMS, Laurent worked 3 years at the Swiss Federal Institute of Technology Zurich (ETHZ) as a Research Associate and Lecturer, managing multidisciplinary natural hazard research projects. Laurent still lectures regularly on geophysics and catastrophe modeling at universities, and gives seminars and invited talks in international meetings. He is a Lecturer and Scientific Collaborator at the University of Fribourg (Switzerland). Laurent co-authored numerous industry publications, reviewed scientific articles and proceeding papers. He holds an MSc in Geology from the University of Lausanne and a PhD in Geophysics from the University of Lausanne and the University of Nantes.

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