Easier access to more weather data can drive insurance growth
With more detailed data, insurers can develop new products that help farmers mitigate losses associated with climate change.
Weather events are becoming more frequent and disastrous for the agriculture industry around the globe. Natural disasters can happen over short periods of time, like the derecho storm in 2020 that devastated about 14 million acres of corn and soybean crops in Iowa with an insurance liability of about $6 billion. Weather events can also cause long-term damage over multiple growing seasons, as the drought and saltwater intrusion from rising sea levels in Vietnam’s Mekong Delta has triggered a decline in rice production for the region.
The effects of weather events like these can be devasting to farmers, and while no one can control the weather, accurately predicting the weather and its effect on crops is possible with the right data to drive the analytics.
Hurricanes, tornadoes, wind, rain, droughts, extreme temperatures, cyclones, floods, hail, and snow all destroy crops in different ways, and every year, these weather events cause more damage. In 2020, there were over 400 natural disasters, and according to Aon, 53 of which were billion-dollar natural disaster events — a significant increase from the 43 events in 2019, and the average of 34 annual events that have occurred since 2000.
Farmers already contend with reduced resources and available land, as well as increased labor and input costs. Weather events exponentially increase their risk and, potentially, costs from losses. Crop insurance is one of the only ways for farmers to mitigate losses from climate, but insurance policies are only available when the risk is properly assessed utilizing the right data.
Farmers need insights related to soil, water, and air temperature to properly determine what crops to plant, where to plant, and how many acres to work. Key factors for planning successful annual crop production include analyzing the available cropping area, or harvested area, and cropping intensity, or the number of harvests per year.
Climate affects each aspect of crop production. While warmer temperatures and higher carbon dioxide levels could have a positive effect and cause some plants to grow faster, most weather events are detrimental to farming and crop yields. Droughts can cause a decrease in yields, while storms, floods, and extreme temperature changes destroy crops. Over time, climate can affect the soil conditions and reduce tillable land through erosion and repeated flooding.
It’s clear that climate has an oversized influence on farming decisions, but the right data and analysis can help farmers and insurers understand how weather patterns and associated natural disasters — along with the potential intensity of these weather events — can impact a growing season.
Data drives the analysis that forecasts weather patterns. The more robust and detailed the data, the more accurate the forecast. The best-case scenario for insurers is to combine data from historic weather events with high-quality real-time information analytics. Currently, models are focused more on visual technologies, such as satellites that take images of the earth, but by expanding the global capacity to capture measurements using innovative methods, the resulting datasets ultimately increase the value and usability of weather information.
Without a strong data foundation, farmers cannot adequately plan for an upcoming growing season, nor can they hedge their risks with insurance policies.
Being able to manage risk through insurance is integral to farming, as climate events can wipe out an entire crop and cause significant loss for families and even whole economies. When farmers are unable to obtain adequate insurance or do not have proper data to assess risk, they may pursue a strategy with more exposure to risk. When farmers have access to insurance policies with risk-based priced premiums, though, farmers have a better understanding of and can mitigate their production risk, which creates incentives to grow more economically viable crops.
Insurance markets in the agriculture industry can write appropriate policies only when sufficient high-quality data is available. Assessing a farmer’s risk requires quantifying their exposure to natural disasters and then using this analysis to size reserves and price policies. Farmers experience catastrophic losses when crops are destroyed, and that loss is amplified when insurance reserves cannot cover the claim because the policy wasn’t priced properly for the risk.
Harvesting the data
Data mining in agriculture drives analytics and forecasts for various crops all over the world, which is particularly beneficial to insurance companies that look to tailor policies for specific risks experienced by an individual farmer. Challenges with accessing and utilizing the data, however, can hinder the ability to provide accurate forecasts and monitoring in a timely manner. Data informs and drives the decision-making process, but data is most useful when it’s in a standardized format that accounts for differences between datasets, such as observation frequency, units of measure, and database structure, as each observation type can come from a multitude of sources.
Each data source has benefits. Satellite imagery, for example, maps land use to include identifying field boundaries and cultivated areas versus natural vegetation while capturing the weather, vegetation, and soil quality. LIDAR on aircraft captures detailed 3-D measurements of the ground and vegetation. Passive microwave sensors aboard satellites gather data on atmospheric and soil moisture. Weather balloons collect critical localized data like wind speed and direction, air pressure, air temperature, relative humidity, and cloud type. Terrestrial radar provides detailed data about crops. IoT sensors essentially create “smart” farms by monitoring soil and crops, controlling irrigation, and detecting insects and pests.
These technologies have not been adopted en masse though, and the availability of Analysis Ready Data (ARD) that contains aligned and geo-rectified data from multiple sources is limited at present. Accurate weather forecasting and nowcasting require integrating or blending data from multiple sources and observation technologies. Currently, though, weather is most often observed in silos, and data is compartmentalized, with some integral technologies being undersampled and underutilized.
Crop insurance relies on timely data
Insurance is a business, and while loss payouts are a major part of the business, so is profitability from pricing policies to cover the risk and having adequate loss reserves to cover claims. Emerging economies like those in Asia and Africa have comparatively few datasets that make managing the risk difficult. More timely data are what drive faster payouts and better risk assessment that’s integral to broader insurance coverage.
With better access to detailed data in different geographies, insurers can develop and offer new products that ultimately help farmers and develop the agriculture sector in those emerging economies. Expanding into these geographies can generate new profits, while improved global data visibility can enable better products in mature markets by providing the advantage of differentiation that results in incremental profits. Developing new products, though, requires robust datasets that may not be accessible at present.
North America and Europe have adequate weather data available, which has resulted in robust crop insurance programs and a healthy catastrophe bond and Insurance-Linked Securities (ILS) marketplace. More mature markets also have better data coverage options that provide timely support for certain perils like flood modeling systems integral to properly assessing the risk for flood insurance.
In emerging economies, these same market opportunities do not exist because data to support similar products is lacking. Within the insurance industry, viable profitable products are data-driven. Having timely access to better-correlated weather data is a fundamental requirement for agriculture insurance, and much of the legacy weather gathering technology does not support products for these areas.
Dataset deficits occur as satellites track some areas more frequently than others. In Asia, Africa, South America, and over oceans, satellites may provide data every 18 to 72 hours while some countries have zero or minimal weather radar stations. Many economies in these regions rely heavily on agriculture, but limited weather forecast and monitoring capabilities hinder crop insurance offerings, which increases the risk of loss for farmers and insurers. =The good news is that additional microwave observation satellites are planned for launch over the next 2-5 years that will significantly increase observation density and timeliness, further improving the viability of new insurance offerings.
Expanding global access to crop insurance plays into farming strategies in a few different ways. Data that reflects the agricultural conditions that a farmer experiences is more likely to provide cost-effective and reliable insurance protection.
As the climate around the globe changes and extreme weather events become more prevalent, the risk to the agriculture industry increases. Farmers need ways to mitigate these risks, and new data sources that provide granular detail on climate are becoming the drivers behind new insurance products. For businesses to maintain competitiveness, they need access to better data in all geographies. Farmers have better risk management practices when insurance companies have adequate data to manage their product offerings, which ultimately benefits us all.
David Gallaher serves as the chief operations officer for Weather Stream. He oversees the development and productization of Weather Stream’s data analytics solutions for commercial, military, and public sector customers. In this capacity, he works with the engineering and scientific teams to create data-based offerings that enable customers to make accurate and timely weather predictions. Prior to joining Weather Stream, Gallaher served in environmental research capacities for several high-profile organizations, including the National Snow and Ice Data Center, Exxon, Advanced Sciences Incorporated, the Petroleum Information Corporation, and the City of Boulder. Gallaher is a noted speaker at academic conferences around the world and has had his research published in over 20 journals. He holds both bachelor’s and master’s degrees in geology.
This article is printed here with permission from Weather Stream.
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