Skyline’s FatTrack Model Ensures Rapid Payout for Jamaican Farmers After Hurricane Beryl

Skyline Partners Ltd., in collaboration with Munich Re, recently showcased the effectiveness of their innovative FatTrack trigger mechanism in providing timely insurance payouts following Hurricane Beryl. The hurricane, which passed close to Jamaica on July 3, 2024, caused significant concern among local farmers. Despite not making landfall, the storm’s proximity still posed a considerable threat. While many traditional event-triggered insurance policies did not respond due to the storm’s failure to meet specific criteria such as radius, windspeed, or minimum pressure, Skyline’s parametric insurance policy successfully triggered a payout.

The insurance, issued to the Jamaican Co-operative Credit Union League (JCCUL), was designed to protect farmers by allowing them to take a payment holiday on micro-loans if extreme weather impacts their ability to repay. The FatTrack mechanism, which calculates payouts based on data from NOAA’s National Hurricane Center, determines the insurance payout by assessing how many insured location-tiles are affected by the hurricane and the storm’s intensity within those tiles. In this case, the policy paid out 45% of its total value, reflecting the storm’s proximity and the resultant damage, despite Beryl not directly hitting the island.

This successful claim underscores the precision and reliability of the FatTrack model, which adjusts payouts based on actual conditions rather than rigid criteria. It demonstrates how parametric insurance, when finely calibrated, can offer more responsive and fair compensation than traditional policies. This development is particularly significant for the Jamaican farming community, offering them critical financial relief during times of crisis and providing reassurance to lenders who might be wary of parametric solutions. Skyline’s approach is a testament to the potential of parametric insurance to address basis risk and provide efficient, timely payouts that align closely with actual losses.