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Cat models do not account for complex hurricane risks: JLT Re

12th July 2018 - Author: Matt Sheehan

Whilst catastrophe models have historically proved accurate for conventional hurricane risks, they have not adequately accounted for events where losses extend beyond wind into areas that are not modelled or well understood, according to a new report by reinsurance broker JLT Re.

The report, which examined the precision of modelled market loss estimates for significant North Atlantic hurricanes since 2004, found that most models performed relatively well for wind events that incurred moderate losses, regardless of landfall.

In contrast, the unprecedented costs of events like Hurricanes Katrina, Ike, and Sandy, where a significant proportion of the losses was caused by flooding or other unforeseen factors, suggest that most catastrophe models have failed to generate accurate loss ranges in such circumstances.

Josh Darr, Lead Meteorologist at JLT Re, said: “This highlights the inherent difficulties modelling companies face in predicting losses for complex hurricane events that strike highly populated urban areas. These types of events often bring unforeseen consequences that cause losses to spiral.”

However, JLT Re also claimed that, as technology advances and more data is collected from these kinds of catastrophe events, accuracy is likely to improve going forward.

“Vendor firms have in recent years drawn on important lessons learned during these events to recalibrate their models and incorporate a whole host of previously un-modelled perils,” Darr added.

Hurricanes Harvey, Irma and Maria provided an important test for the latest generation of hurricane models, and while the accuracy of modelled losses for the events were mixed, certain results revealed some encouraging signs given the levels of complexities involved.

The graph below, taken from JLT Re’s report, shows the evolution of modelled loss estimates for select U.S hurricanes from 2004 to 2017.

JLT Re cat model losses graph

David Flandro, Global Head of Analytics at JLT Re, commented on the results: “This snapshot goes some way to explaining why the industry loss estimates provided by catastrophe modelling firms have led to general scepticism within the (re)insurance market over the last 15 years or so.

“At first glance, there is an overriding trend towards significant loss underestimation (the 2017 hurricanes apart), and it is not even immediately apparent that the range of loss estimates narrows during the lifespan of storms, or that they always become more accurate.”

Keith Leung, Head of Catastrophe Modelling – International at JLT Re, also commented: “2017 reinforced the importance of understanding differences between estimates. Working with a range of modelled, post-event views can be valuable as long as the important drivers are clearly highlighted, particularly in situations where significant divergences occur.

“Catastrophe modelling firms can assist the market further here by better communicating the key drivers of loss within each estimate and providing more transparency around the various assumptions being applied. It is likewise incumbent on market participants to review rigorously, or even challenge, some of the more extreme loss estimates released by modelling firms.”

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