The use of unmanned aircraft to capture weather data could be about to transform risk transfer.
Improved weather data is leading to more dynamic and precise risk transfer strategies.
Advances in data capture have given rise to the development and use of parametric-based products, as well as greater optionality around weather parameter triggers.
As a result, weather risk transfer is growing among companies that may need to recover capital, or mitigate the losses they face as a result of abnormal weather.
Take the West African growers who produce around 70 per cent of the world’s cocoa.
The 2015-2016 season was marred by particularly dry weather. High temperatures, low rainfall, and strong, dry seasonal winds led to a massive deficit in cocoa production – it plunged 12.6 per cent from the previous year to 226,000 tons – not to mention a marked fall in cocoa quality.
The adoption of weather hedging is allowing large-scale cocoa producers to purchase products that protect them financially against the losses they would assume in an unfavourable year.
These products can target any level in the supply chain – from protecting the obvious risk (production losses) through to associated risks (e.g. distribution or business interruption losses).
Cocoa producers might prefer a product that triggers in the event of low rainfall, heavy wind shear and/or high temperatures. For cocoa buyers, a hedge could include a secondary trigger that responds to hikes in cocoa prices.
In 2014, an unmanned aircraft called Coyote was dropped into the eye of Hurricane Eduardo off the Atlantic coast. The data captured ran to depths previously inaccessible by manned planes.
This information greatly facilitated the transfer of catastrophic and non-catastrophic risks and weather risks to the insurance-linked securities marketplace. The same goes for contingent business interruption and business interruption risks.
Imagine if a Coyote 2 could be launched into the centre of a tropical depression, which forms in the Atlantic and moves towards Florida. The data could be used to more accurately determine the strength of the weather system, and the direction it will head in. This could result in more robust Live-CAT products for companies looking to hedge these kinds of events.
Could these drones be used to better understand ground temperature changes, micro-climate feedback mechanisms, or potentially flood mitigation?
But one thing’s certain: the more robust the data, the cleaner parametric products can be, and the easier it will become to determine if an event has been triggered.
Please contact Ryan Fitzpatrick on +1 646 362 4654 or at email@example.com for more information.