Agricultural risk technology makes advances

In the U.S., the Department of Agriculture’s Risk Management Agency (RMA) collects numerous categories of data about a variety of crops, also including assessments of damage risks due to hurricanes.

While the RMA’s data sets a certain standard to determine risk for agricultural insurance coverage, technology providers and technology operations by insurers themselves are making this information more precise.

AXA Climate, which offers parametric insurance providing compensation for weather and climate risks that come to pass, uses a combination of types of data, handled using cloud resources to analyze weather and crops, one year at a time, says Sylvain Coutu, head of agriculture insurance at the firm.

Alongside its parametric insurance, AXA Climate also offers weather derivatives that provide support in the event of extreme hot or cold weather patterns affecting crops. The parametric insurance operation creates climate forecasts. The derivatives side takes satellite data and weather information to assess short term risk, Coutu explains. They’re currently determining risks for 2023, rather than attempting to predict the next 10 or 20 years, he adds. 

AXA Climate applies weather and crop analyses to historical data, but also brings in a manual element to produce what Coutu calls “hybrid data.” 

“Let’s say you have 1,000 fields in your portfolio,” he says. “Traditionally at the end of the season, you need to send people to each and every field. We take a satellite image of each of these fields and calculate the yield on each of these fields from space. Depending on the uncertainty in our satellite based analysis, we will send people to some of these fields to do what we call a crop cut. When you cut part of the field, you weigh the grain and you extrapolate and calculate by hand the physical production of the field.”

The measurements from the crop cut combined with satellite data reduces fraud and brings scientific calculation, rather than just negotiation, to claims assessment, according to Coutu. This process can identify smaller areas with lower or higher yields than the rest of a farm. AXA Climate’s processes also use weather station data and soil databases. AXA Climate launched three years ago after starting as AXA Parametric about six years ago.

John Bourne, vice president, Ceres Imaging

Ceres Imaging, an agricultural services and financial technology company for the past 10 years, entered the insurance industry two years ago with a product using artificial intelligence to analyze satellite data of farms to rate and help reduce risks, according to John Bourne, vice president at the company.

Working in a research partnership with UC Davis, Ceres (pronounced “series”) used its proprietary high resolution image capture to develop yield risk and disease risk prediction insurance products. Convolutional neural networks, a form of AI used to analyze images, identifies ground cover and soil separately from crops to get accurate measurements, according to Bourne. Ceres also applies algorithms to the images, finding indicators such as thermal heat emanating from crops, where changes could indicate irrigation issues or other less noticeable threats. This leverages image data to predict impact on crop yields. 

In addition, all the new information Ceres produces actually streamlines the underwriting process for agricultural insurance with its more complete analysis of risk, according to Bourne.

Farmers Mutual Hail Insurance Company of Iowa (FMH) entered the risk technology space in 2015 with Precision Crop Insurance Solutions, which supports and eases reporting of data to the RMA. FMH built on development done by John Deere Insurance Company and John Deere Risk Protection, which it acquired in 2015, to offer its solutions product, according to David DeCapp, senior vice president of marketing at FMH.

Farm management systems can use Precision Crop Insurance Solutions in the form of an API, taking information the system captures in the field and feeding it directly to FMH. From there, FMH agents can review and verify data, then document it for the farmer and file it with the RMA, according to DeCapp. 

“An agent is able to differentiate with that customer or prospective customer to be able to more seamlessly, accurately and conveniently process the data that is required,” he says. “You eliminate a lot of double entry. You eliminate any miskeying.” This streamlining extends to claims processing, leveraging collected data to adjust claims “quickly and accurately, versus having to aggregate any number of other production reports that the farmer would otherwise have to produce,” DeCapp adds.

For example, without the technology, a farm might report that it planted 50 acres with corn. Precision Crop Insurance Solutions, using collected data, finds that actually just 45.4 acres out of the 50 produced corn that could be harvested. 

“You gain the advantage of that accuracy in years going forward rather than either over reporting or under reporting based on just using a map and saying, ‘Here’s my field and it’s 50 acres, so therefore I planted 50 acres of corn,'” says DeCapp.

FMH has plans to branch out with its Precision Crop Insurance Solutions technology. The company is working on a capability to review third-party digital agriculture functions, which would supplement its current risk data offering. “Given the continuously changing and evolving nature of the digital agriculture industry, this unit is critical to ensure we are evaluating state of the art solutions for the risk management needs of our agents and customers,” says DeCapp.