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Luzi Hitz, chief executive officer of PERILS
24 October 2018 Insurance

Real-time data could create live cat cover opportunities

Short-term trading and the buying of live catastrophe coverage could become much more prevalent with the advent of real-time data—but it is still early days, Luzi Hitz, chief executive officer of PERILS, told Baden-Baden Today.

“If there is a hurricane or windstorm approaching, and billions of dollars of predicted market losses, people will start short-term trading and buy hedges using this kind of information. We are not quite at that stage yet, but I could imagine that there will be much more of this one day,” Hitz said.

He suggested there could be some shift from reinsurance and retrocession being usually bought at January 1 and renewed once a year, to its being bought very short term for very specific events.

“Where you have pre-event loss estimates it may indicate it’s a good idea to buy a hedge,” Hitz added.

Although PERILS’ core activity is as a data collector and aggregator for natural catastrophe losses post-event, it has been developing Wind-Jeannie, its forecasting platform, which provides forecasts of the insured property market loss for the following 72 hours.

PERILS launched Wind-Jeannie Australia on October 22, with each forecast divided into Australian state and postcode.

Wind-Jeannie Europe is entering its fourth European windstorm season, and PERILS has updated the model with data from events such as January 2018 storms Friederike and Burglind, along with other storms captured since the 2016 update.

Friederike created a market loss of €1.675 billion, and this was used to help recalibrate the model, Hitz explained.

“Numerical weather product models have become so much more sophisticated and more accurate than in the past. The insurance industry should use this more to manage its exposure or to prepare for big events,” said Hitz.

With Wind-Jeannie, Hitz explained, damage degrees are plotted against the windspeeds that occur in particular zones, which can provide an industry loss forecast not dissimilar from a weather forecast.

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