The Demex Group, a climate risk management platform, has launched a snowfall insurance product.
Demex considers itself a leading innovator in the field of climate risk. This also encompasses sustainable finance and climate risk transfer.
Its technology platform instantly performs climate assessments for every point around the world and then integrated client data and scalable analytics to develop and offering of financial instruments that are backed by a network of trusted capital partners.
Due to the changing climate and changing nature of winter storms, Demex said that revenue and operating costs in snow-sensitive businesses are experiencing unexpected volatility driven by the changing natural of winter storms.
There are two key types of coverage including in the new offering. Demex Snow Insurance was created for snow-dependent businesses; claims are triggered when snowfall is low. Demex Cost Control Insurance service property owners, facility managers and municipalities, claims are triggered when snowfall is extremely high.
Carlos A. Oliveras, head of insurance at Demex, said, “Unpredictable volatility creates significant challenges for commercial property owners, facilities managers, municipalities, and snow removal contractors alike.
“These businesses are particularly vulnerable. Winters with unexpectedly heavy snowfall boost cost for some and years with little snow destroy revenue for others. Snow insurance serves as a shock absorber for snow-sensitive businesses.”
This kind of offering is particularly import amid a time of increasing prevalence of extreme and unusual weather events. As such, there is a growing demand for climate intelligence so insurers can act more quickly and efficiently.
Athenium Analytics, a provider of climate intelligence and enterprise risk analytics, recently launched a historical tornado data set available through the Esri ArcGIS Marketplace.
Athenium said the comprehensive tornadic data set allows Esri users to better analyse and predict catastrophic losses. With regard to tornado’s in particular, despite their frequency in the US and potential for disruption, they are “notoriously” difficult to forecast.
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