Risk Data Management in Agriculture Is Changing Quickly
Risk data management in agriculture is changing for several related reasons, including the sheer volume of useful data that can now be unsiloed, collected, and integrated. As a result, agricultural professionals need to find new ways to manage and assess risk data.
According to the OECD (Organisation for Economic Co-operation and Development),
“There is a need for the agricultural sector to become more resilient to production and market risks. [However] it is also important that risk management policies do not try to increase the incomes of farmers now at the expense of a resilient and sustainable agricultural sector in the future.”
In other words, agricultural professionals need to be able to make realistic, real-time assessments of a farming operation’s current risk levels and long-term viability. With modern risk data management tools and practices, lenders, investors, and other ag finance institutions can be ahead of the curve when it comes to managing risk.
Risk Data Management in Agriculture is Changing – Because It Needs To
The North Central Extension Risk Management Education Center at the University of Nebraska is one of only five centers of its kind in the country. It’s funded by the USDA, and is designed to “help producers achieve real risk management results and improve farm profitability and business success.” Its director, Bradley D. Lubben, notes that recent challenges in the agricultural sector have been “almost unprecedented”:
“From financial challenges to production and market shocks to public health scares and policy developments, agriculture has had to respond and adapt to a wide range of issues … like profitability, cost control, weather, and production decisions.”
Some of the most pressing issues include the growing prevalence of flood damage in agriculture and the impacts of climate change on agriculture water risk. Because these risks don’t follow historical trends and predictable weather patterns, new strategies are needed to collect and integrate data and make informed decisions about risk. The following factors are key to understanding the current state of risk data management in agriculture:
Digitalization Is Growing
First, digitalization is rapidly transforming the agricultural industry around the world. This includes everything from precision agriculture technologies on traditional parcels of land to indoor farming and controlled-environment agriculture (CEA). As a 2021 report in the Sustainability Journal puts it:
“Digital technologies offer a potential solution to improve sustainability—economic, social, and environmental—of agri-food systems around the globe.”
Ag professionals who make use of digital technology will have a competitive advantage over those that don’t, cutting down on the time it takes to approve loans, research land and water rights, and perform accurate asset valuations. By digitizing their agricultural data and integrating third-party data sets, ag finance professionals can have real-time access to the information they need in an easy-to-understand, geospatial format.
Speed Is Currency
Digitalization leads to the next component of successful risk data management, which is speed. As climate change disrupts weather patterns in many major agricultural areas, ag professionals need to be prepared to adapt with little to no advance notice.
According to the OECD-FAO Agricultural Outlook 2019-2028:
“Extreme climate events such as heatwaves, droughts, and heavy rainfall will likely occur more frequently and last longer in many areas.”
Ag professionals need to be prepared for the rapid onset of drought, the rollout of new regulatory policies like SGMA, and the uncertainty of water deliveries in water-stressed regions. Other wildcards include wildfires, seawater intrusion, and land subsidence. As these risks become more widespread, speed will be a currency, and the producers who can respond the fastest will be better suited to withstand new types of risk.
Depth + Granularity
Finally, risk data management requires a level of depth and granularity that has been absent from agricultural data management practices in the past. A U.S. AID report on smallholder agriculture points out how granular data and predictive analytics can be used to provide “regionally-specific insights” to local farmers:
“The Aclimate Colombia project …. produced analytics that predicted a major dry period would disrupt the upcoming growing season…. Many farmers used these … insights to guide their decision making, leading to yields that were significantly higher than those of farmers who ignored the Aclimate recommendations.”
In the U.S., ag professionals can use geospatial tools to understand ever-growing geospatial risks on specific parcels of land in their portfolios, accessing data on water rights, water quality, and other relevant data sets. They can then share these parcel-specific insights with other stakeholders, including borrowers themselves, to improve resiliency and mitigate climate risk.
Risk Data Management Can Put Bank Data into Context
The best risk data management practices can be used to “acclimate” existing data sets, or put bank data into context by bringing in new layers of information. An agricultural lender, for example, could incorporate data on water rights, watershed boundaries, and drought risk into their loan decisioning process, rather than depending entirely on the financial risk of the borrower to decide whether to approve or deny a loan.
Being able to merge third-party risk data with proprietary bank data is a key function for modern risk data management systems to have. By putting existing bank data into context, ag professionals can unlock advanced risk analytics and gain deeper insights into the farms in their portfolios.
How GIS Connect Can Support Risk Data Management
GIS Connect is a map-based SaaS platform and data management tool that’s designed specifically to meet the needs of the modern agricultural finance professional. Users can monitor their portfolio to identify material risks, collaborate with other team members with exportable reports and attachments, and integrate third-party data sets to add context to existing data, such as water-restricted areas, flood zones, water rights, endangered species zones, well reports, and more.
GIS Connect is cloud-based and built with bank-grade security, making it easy for users to unlock new insights from proprietary data without unlocking the data itself. Users can search by parcel, borrower, or farming operation, or simply use the intuitive map-based interface to view detailed information without ever leaving the map. Other tools include cohort analysis, workflow management, and managerial report generation.
GIS Connect empowers ESG reporting because it brings bank data and third-party risk data together, making a business able to adapt to the still-solidifying reporting requirements, which can cause a great deal of uncertainty. As governments roll out new ESG reporting requirements and mandatory climate risk disclosures, ag finance institutions that already have a data management strategy in place will be ahead of the curve.
The Bottom Line
Risk data management in agriculture is changing rapidly, as new digital technologies make it possible to gather more data than ever before and analyze it all in one place. In addition, the growing risks of climate change and associated regulatory requirements make it imperative for ag finance institutions to be able to respond quickly to new risk factors and understand existing risk factors at a deeper, more granular level.
AQUAOSO’s GIS Connect tool is specifically designed for agricultural professionals, with a map-based interface that presents risk data in an easy-to-understand format. Lenders and investors can use it to inform their investment decisions, monitor their portfolios for new climate risks, or work with borrowers to reduce existing risks.
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