Weather Risk and Big Data

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By : admin |June 01, 2018 |weather-report |0 Comment

Weather Analytics (soon to be Athenium Analytics after our acquisition of and merger with Athenium! BIG NEWS) has joined the Weather Risk Management Association (WRMA) and will attend the 20th WRMA conference June 6th-8th in Miami, FL. Weather Analytics is advancing the services and sectors covered under the weather risk market through Big Data.

Most are familiar with traditional catastrophic weather risk. Wind causing trees to fall on houses, hail striking cars and rivers flooding homes all demonstrate how dangerous mother nature can be. Although these events don’t occur too often, they can be devastating to those affected. That’s why insurance policies are purchased to protect property for these low probability, high-impact losses, transferring the catastrophic weather risk.

Insurers need Big Data as greater understanding of the risks leads to more efficient underwriting and claims processes. Weather Analytics’ high-resolution data and analysis have expertly aided assessment of this class of risk for years. Our clients utilize the product suite through user-friendly applications. Gauge provides risk scoring for underwriting support based on our historical weather data. Beacon allows carriers to alert their insureds of incoming hazardous weather for purposes of loss mitigation and claims preparation. Dexter, a post-event forensics tool, recently gave a broader view of the hail that occurred in the Northeast on May 15th, 2018. Notice, in the image below, the resolution (0.6×0.6 mile grids) providing more information to insurers compared to the traditional observations in purple.

dexter, Weather analytics, risk, hail, insurtech

Non-Catastrophic Weather Risk

So what about non-catastrophic weather risk? Think of a concert being canceled due to rain. The stadium loses money when they don’t get to charge $10 for hot dogs. This is a risk to the stadium’s anticipated yearly revenue. Other examples include a lack of snowfall deterring skiers from buying lift tickets, warm winters lowering natural gas demand and clouds decreasing solar power production. These events tend to happen often, but without catastrophic financial effect (high probability, low impact).

Investment vehicles like weather derivatives may be used to hedge these non-cat risks. Weather derivatives are financial contracts based on an underlying meteorological variable. Standardized contracts are traded through exchanges like the Chicago Mercantile Exchange, while more customizable contracts are found in the Over-The-Counter (OTC) market. Buyers usually pay a premium and receive a pay out if certain weather conditions occur in a certain area and time. Here’s an example:

A frozen lemonade company recognizes that when summer temperatures in the Northeast are cooler than normal, the revenue in that region drops. The company purchases a weather derivative that would payout if cooler temperatures occur, replacing the revenue lost when not as many people need a delicious frozen drink. If the summer turned out to be a scorcher, revenues will likely be through the roof and the company wouldn’t mind the lost premium money.

data, global, risk, weather analytics, insurtech, derivatives

Big Data to the Rescue!

Reinsurers and other weather derivatives dealers rely on historical data to accurately price contracts. Increases in the granularity of the weather data allow for OTC contracts to more efficiently hedge the risk of the individual. That’s where Weather Analytics comes in–delivering global climate intelligence by providing statistically stable, gap-free data formed by an extensive collection of historical, current and forecasted weather content, coupled with proprietary analytics and methodologies. The hourly ground station and 30 km gridded data covers 39 years of hyper-local weather variables, allowing dealers to address their clients’ specific global weather risk.
For more information how Weather Analytics assists top weather risk market participants, e-mail me here: matthew.davey@weatheranalytics.com

Matt Davey
Lead for Weather Derivatives