Decision Support Fintech Can Save Ag Lenders Time and Money
The modern financial business landscape is full of tough decisions, many of which are time-sensitive. The most valuable asset for making smart business decisions is being well informed. Unfortunately, given the vast amount of necessary but siloed decision support information, remaining well informed can be time-consuming and costly.
For ag finance professionals, the need is even more acute. As more risk data and third-party analytics become available, they give information to the ag finance sector. However, this information is usually standalone and is hard to splice, organize, and manage together with proprietary data such as borrower data, as well as other crucial information such as appraisal and audit reports.
What is left is tediously-gathered and still-siloed data that is not as actionable as it could be.
Another growing category of risk is climate change and water stress impacts on farmland. As these factors become more severe across the western US, lenders must navigate an increasingly risky and volatile environment.
Old methods of assessing financial risk are no longer sufficient. According to a Cornell-led study, “global farming productivity is 21% lower than it could have been without climate change. This is the equivalent of losing about seven years of farm productivity increases since the 1960s.”
As both ___ and climate risks continue to endanger the bottom line of growers, delinquency and default become more common.
The takeaway here is that there are many growing risk factors in U.S. agriculture finance. Digital decision support fintech is a pathway to gathering, analyzing, and viewing the siloed data necessary for risk management.
For ag lenders seeking to de-risk their portfolios, decision support fintech offers a solution. By helping make sense of all the relevant risk factors together, decision support tools can empower ag finance professionals to re-shape their portfolios for the better.
This article will first define decision support, then explain how it can benefit financial institutions and the attributes that are key to picking the right tool in agricultural finance.
What is Decision Support?
While decision support is a broad term, in the ag space the definition is more specific. According to the USGS Upper Midwest Environmental Sciences Center (UMESC), decision support can be looked at as, “a spatially based computer application or data that assists a researcher or manager in making decisions.”
At its core, decision support is software that empowers an analyst by allowing them to focus on insight generation and strategy rather than data collection and processing.
By organizing and presenting relevant information in an accessible way, it can unlock insights and inspire approaches to address novel challenges. Critically, decision support is not an AI that tells users what they should do. As the name suggests, these tools don’t replace decision-makers, but rather support them to make more informed decisions more quickly.
An example of this in ag finance is deciding whether or not to carry out a loan or how to manage a relationship with a borrower.
Different tools are specialized to empower different user types. The tool most useful for the ag sector would likely look quite different from the tool most useful to the logistics sector. Picking the right tool for a company’s needs is critical. Purpose-built tools yield the most results.
While a recent product of the digital age, decision support is already demonstrating its utility. According to a March 2020 study in the journal Computers and Electronics in Agriculture, the value of Agriculture Decision Support Services (ADSS) was high.
“Due to the capability of processing a large amount of agricultural data and handling complex environment, and ADSS is very helpful for assisting farmers in performing various agricultural activities.”
Applying decision support to other spheres of the ag sector can be similarly useful.
How Can Decision Support Fintech Save Finance Professionals Time and Money?
Decision support fintech helps manage the two greatest challenges when it comes to ag finance:
- Scale of risk
- Complexity of risk
A portfolio with many millions of dollars of assets spread across hundreds or thousands of miles is so large that making sense of how continually changing local conditions impact the bottom line can be difficult.
Decision support fintech relieves this stress by continually processing the dynamic changes and risks within a portfolio, compiling comprehensive risk profiles, and making that information easily accessible to finance professionals at the click of a mouse or touch of a screen.
On a more foundational level, aggregating all the necessary information to make informed decisions on every plot can be prohibitively resource-intensive. Compiling digital and analog records from dozens of different sources, processing them into compatible formats, and maintaining the database to include all the latest updates is extremely costly to do in-house.
By offloading this responsibility to a decision support service, financial institutions can spend more time building business intelligence and less time tracking down data, only to have to build a process in-house.
With access to the deep database of risk indicators that data acclimation provides, decision support can unlock critical insights otherwise obscured by the complexity of risk factor interactions. By un-siloing and integrating risk data, loan portfolios can be acclimated and a more holistic picture comes into view.
A dynamic view of how all these variables interact with each specific parcel through decision support fintech offers instant access to insights that could take weeks to discover otherwise. This business intelligence can be applied for better loan decisioning and mitigation building.
What Attributes Make the Best Decision Support Tools in Agriculture?
A hyper-local, multilayered approach is becoming increasingly common in risk assessment. When FEMA revised their methodology for calculating flood insurance rates earlier this year, they based their approach on spatial relationships and overlapping risk factors.
As explained by their April 2021 report, “the risk of large loss events is greater in areas with a higher concentration of policies. In order to reflect these differences in risk due to differences in policy concentration, Milliman developed concentration risk loads that vary by geographic area.”
In addition, it noted that “property characteristics rating factors include those rating variables that are based on characteristics of the insured property other than its location or policy terms.”
While flood insurance and ag lending have several important differences, both must contend with the impacts of climate change. As such, a multi-factor geospatial approach is vital.
Combining 1st party financial records with 3rd party risk datasets – with climate and water datasets being a mere portion – data acclimation gives ag finance professionals the critical insights needed to identify points of risk within their portfolios in a groundbreaking geospatial medium.
Given the rapidly shifting landscape, dynamic updates are critical for a decision support system to empower agility in ag. Presenting information clearly and accessibly is also essential. One of the most effective ways to do so is through data visualization maps. By presenting information visually, ag finance professionals can quickly process a high density of data and quickly make sense of the most relevant elements.
The Bottom Line
Decision support fintech is a valuable tool for ag finance professionals to evaluate risk at the parcel and portfolio levels. Utilizing geospatial data on environmental and social aspects of climate and water risk, decision support fintech provides a holistic profile of relevant considerations. By employing the right tool financial institutions can save time and money by making smarter decisions more efficiently.
AQUAOSO’s tools aid Farm Credit and commercial lenders’ decision support and are purpose-built to help ag finance professionals manage their risk and data.
The GIS Connect platform allows users to integrate third-party data sets with their own data in a secure GIS data management platform. View loan, investment, supplier, and appraisal/audit data in a single geospatial view with best-of-breed land and climate data integrated through secure APIs. Manage board and regulatory requirements with automated geospatial data management, information collection workflows, and reporting.
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