New tools bring new insights to ag lending.
By Jim O’Brien
The current state of the economy has many small farmers experiencing déjà vu from the 1980s. A recession, skyrocketing inflation and environmental issues are straining farmers’ ability to operate and compete across the global marketplace. In addition, many farmers struggle to secure necessary capital.
Banks and farmers are welcoming tools that change the arc of recent history. The 1980s crisis put both banks and farmers in difficult positions. Due to the challenging times, many small farmers were delinquent on loans or went bankrupt. By the end of the decade, an estimated 300,000 farmers defaulted on their loans, and more banks failed in 1985 than in any year since the 1930s. The crisis ushered in an era of tense relationships between banks and small farmers. Fast forward to 2022 and too many farmers now struggle to secure loans and necessary capital to keep their operations afloat.
New farm data revolutionizing risk assessment
For banks, assessing agricultural risk has historically been complex due to a lack of standardized farm production information. Further complicating the challenge is the fact that gathering the needed information on a farm is largely manual, time-consuming and error prone. Many community banks do not have the bandwidth to conduct in-depth appraisals on each farm that applies for a loan.
The good news is that we have reached a new inflection point with modern technology. Agricultural data solutions can help risk-averse banks provide loans to small farmers, meaning they are in a better position to serve their customers than they were 40 years ago.
New tools collect and analyze dozens of farm-specific data points that are traditionally left out of the loan process. These provide a more nuanced view of a farm’s risk, and include features such as:
Historical level field data models. Accurately assess farm production and performance.
Free cash flow analysis. Review the capital expense of an operation and profit of farmland productivity.
Risk-based pricing. Establish standards and benchmarks for farming customers to better determine risk.
Production volatility. Measure production variability on a micro-level, comparing farms against those with similar characteristics in similar production regions.
Data solutions can also review information including weather patterns, soil carbon levels and land management practices such as no-till, to determine a farm’s environmental impact. Banks can use this assessment to inform them in an era when risk factors such as extreme weather present concerns.
Each of these elements can help banks create a clear farm risk score that is scientifically validated and easy to compare between farms.
Innovative data solutions are changing lending
The parallels between the 80’s farm crisis and our contemporary challenges are major concerns. But community banks can tackle these head-on. Banks benefit when they take a new approach to ag lending by using modern data collection tools that consider farm-specific information.
By using a data-backed solution, ag lenders can gain a complete picture of a farm’s risk level and ensure their lending decisions are sound. In turn, they can provide loans to small farmers while avoiding the burned bridges from the 80’s.
Jim O’Brien is the CEO of Agrograph, a global agrifinance company based in Madison, Wisconsin.
