Risk modelling company RMS has seen an increase in demand for its modelling from primary insurers looking to get a better understanding of their risk selection and the pricing of smaller risks, Laurent Marescot, senior director, RMS, told Intelligent Insurer.
Marescot said that one driver of this has been the nature of repeat losses from similar events, specifically flood, in recent years.
“Traditionally, cat model analytics is primarily used to underwrite large commercial and industrial exposures, but now insurers also want to understand their retail and small commercial risks better at the point of underwriting,” he said.
“We see this especially for flood, which is a high-hazard gradient peril, in markets with low flood insurance penetration such as Italy or Germany.
“It can also be seen in France where, despite the presence of the national nat cat scheme, insurers want to better understand their tariffication and make more informed strategic underwriting decisions, in addition to managing their retention.”
He added that, since it is not possible to run a full probabilistic model for retail underwriting, RMS derived specific data products from its models to help this market segment, such as hazard maps or pre-compiled rating tables (such as loss costs).
“This is a game-changer in the way underwriting is done,” Marescot said.
He added that there is a broader trend across Europe to achieve a complete and comprehensive view across all natural catastrophe perils in the region.
“This is not only a concern for reinsurance, but also for insurance. The market needs suitable tools to manage accumulation and better plan diversification,” he said.
“Beyond managing wind risk, which remains the key peril for reinsurance and Solvency II, there is a large focus on flood, especially in the light of repeated damaging events as we saw again in October in France and Italy.”
He said that, in some countries, such as Italy, flood insurance penetration is very low, with fewer than 5 percent of residential buildings covered for this peril. RMS covers Italy as a part of its pan-Europe flood model coverage and Marescot said the firm is seeing traction in the Italian market to use this tool to estimate a suitable tariffication, grow new business profitability and to help narrow the protection gap.
“The market needs suitable tools to manage accumulation and better plan diversification.” Laurent Marescot, RMSFlood risk assessment
In September RMS released its new EU severe convective storm model, covering hail, straight-line wind and tornado. Together with EU flood, windstorm and quake, this provides the first and only probabilistic model view in the industry that covers all main nat cat perils (over 95 percent of average annual loss) across over 15 countries in Europe (over 98 percent of property gross written premium).
RMS updated its flood model in Europe this year, implementing the latest inundation model using the full shallow water equations along with other updates.
Daniel Bernet, product manager, RMS, stressed that RMS has been building flood models for over 20 years. He said that its first models released on RiskLink for the UK, Belgium and Germany capitalised on research, data, and technology available at the time of release and during the update.
“Recognising the market’s need for more granular, accurate, and realistic flood risk assessment, we have built and released the high definition (HD) models in 2016, our next generation flood models,” Bernet explained.
“Since then, we have further extended the pan-European model coverage to include Ireland and Italy in 2018, and implemented the latest data and methodological advancements in 2020.”
The RMS EU Flood (EUFL) HD model tackles key challenges in flood modelling with what he describes as innovative solutions.
“We start by modelling precipitation continuously over a period of 50,000 years. Thereby, we can account for antecedent conditions that play an important role in determining the severity of flood events.
“For instance, if the precipitation of the 2002 flood event in Central and Eastern Europe occurred in combination with antecedent wetness conditions from the 2013 event, losses would have been more than 400 percent higher,” he said.
“The industry has appreciated the key benefits of the EUFL HD models.”Flood defence
The model captures factors including seasonality, temporal clustering of events, and spatial correlations within the whole pan-European domain.
“The latter is particularly important for tail risks of pan-European exposure, as 25 percent of past recorded events affected more than three countries simultaneously,” Bernet said.
Another important advancement is RMS’s flood defence model, which can be used to determine the severity and extent of flood events.
“First of all, it is based on a comprehensive collection of available flood defence data that covers roughly 30 percent of the major rivers in the model domain. Since for the remaining 70 percent of the major river sections there is no information available, we have developed a method to estimate these defence levels based on exposure at risk, population density, and the size of the river,” he explained.
“Second, we have come up with a way to allow the user to adjust these flood defence levels, to incorporate local site knowledge, build a bespoke view of risk, or to explore sensitivities around the defence assumptions.”
Bernet said that RMS has advanced EU flood modelling by creating more accurate and granular results, while providing the users with more flexibility to incorporate their own expertise. A good example of the former is the updated inundation model in the latest EUFL HD release, which is able to capture all hydrodynamic effects when assessing the extent and intensity of flood events, overall providing a more realistic representation of flood hazard.
“Another example is the use of stochastic exposure disaggregation functionality that places low-resolution and aggregate exposure to likely locations, and then subjecting these to the high-resolution flood footprints, rather than aggregating hazard layers to unrealistic mean values.
“In terms of flexibility, it is worth calling out the option for the users to define their own time-based policy conditions for reinsurance treaties, such as a flexible hours clause,” he said.
“The feedback from the industry to these latest innovations has been great. The industry has appreciated the key benefits of the EUFL HD models such as more granular, realistic, robust, and much more detailed results, coupled with enhanced flexibility to create a bespoke view of risk.
“The release of the models in Risk Modeler is a huge leap forward, as the execution is unified for our RiskLink and HD models, has become much more intuitive and efficient, and has many additional benefits such as easy deployment, lower total cost of ownership, and more,” he concluded.
RMS, Flood, Catastrophe, Insurance, Reinsurance, Laurent Marescot, Europe