Not All AgFintechs Are The Same
consider ag lending, they must assess these five critical factors during the
data vendor evaluation process
According to Jack
Henry’s 2023 Benchmark study, 95% of all financial institutions plan
to enhance their lending capabilities. To do so, many of them plan to increase
their technology spend over the next two years. Much of the focus has been
small business and commercial lending, especially as markets like mortgage see
declines amid record interest rate hikes. However, one overlooked area is ag
The value of farmland continues to
soar, making it a compelling investment. Last year alone, the average value of
farmland across the United States rose by 14%. In states like Iowa and Kansas,
the value of an average farm acre increased
by 22.4% and 25.2%, respectively.
Additionally, the U.S.
Department of Agriculture cites that one-third of the 3.4
million farmers in America are over 65 years old. As these farmers retire,
there is a significant opportunity for banks to capture this generational
wealth transfer and support the next generation of farmers who will require
loans and capital to establish their own operations or continue those they
Despite the attractiveness of ag lending, many traditional financial
institutions are reluctant, primarily because they are unfamiliar with this
industry. This market also poses a challenge for most lenders. Unlike
traditional risk assessment processes for commercial loans, agriculture lending
requires additional farm-specific information such as yield, crop diversity,
grain market insights and ratio of owned versus leased farmland, to name a few.
These unique data points are not reported by analytics companies,
publicly available to investors, or standardized by any measure—only adding to
the complexity of the time-consuming process of assessing risk for agricultural
This means financial institutions must look to
fintechs. However, as the space becomes increasingly crowded with tech
companies “band wagoning,” the pool of credible agfintechs remains small. In
fact, the Independent Community Bankers of America
(ICBA) pointed to a growing need among its members earlier
Adding to this challenge, partnering with fintechs in general has its
own set of risks. Even federal regulators have noted this, recently releasing guidance
for working with third-party companies, particularly as it relates to
risk and compliance.
Alas, banks are increasingly turning to fintechs
to stay competitive, innovate and deliver enhanced services to their customers
– including ag lending. But not all agfintechs are the same. The process of
selecting the right partner can be a complex undertaking that requires careful
consideration and strategic planning.
To ensure a successful partnership, banks must
assess several critical factors during the data vendor evaluation process:
- Define Objectives
embarking on the search for a fintech, banks must clearly outline its
objectives and goals. Having a well-defined vision will guide their search.
also important to set realistic expectations related to data accuracy. Data
modeling, especially for natural environments, is inherently complex and ever
changing. For instance, weather forecasts are an important metric to assess
risk within ag lending, but it’s only 80% accurate on that day. For long term
forecasts the numbers are even worse, citing research from the US government
National Weather Service Weather Prediction Center showing a
steep decline in accuracy from three to seven days with accuracy dropping down
to only 0.003%.
entering ag lending, they must move beyond Loss Aversion bias, or the belief
that a real or perceived loss is more severe than a real or perceived
equivalent gain. Ultimately, there must be a high-level of trust and complete
transparency within the bank-fintech relationship. In addition to an acceptance
of living with(in) accuracy for data modeling.
must also evaluate fintechs based on their compatibility with their
internal culture, values and strategic direction.
Look for alignment in terms of mission, vision and commitment to innovation.
Banks must also assess the compatibility of the fintech’s technology with its
existing infrastructure. Seamless integration and scalability are crucial for
ensuring a smooth implementation process.
and transparent communication is also key. Banks should discuss expectations,
deliverables, timelines and support services before entering into a
partnership. And finally, banks should choose a fintech company that demonstrates a long-term vision and commitment to building
a sustainable, mutually beneficial relationship.
- Expertise and Track Record
must also research the fintech’s expertise within agricultural lending. It’s
not enough to demonstrate a knowledge of data science; fintechs must have a
deep understanding of the industry.
must also examine their track record of successful implementations, client
relationships and industry recognition. A proven history of delivering
solutions that align with the bank’s needs is a strong indicator of their
be fooled by large sums of venture capital raised. Some of the largest agtech
companies as reported by AgFunderNews have been
hounded by massive drops in valuation despite high hopes and media hype to the
contrary. Instead, seek conversations with the CEO or founders to ensure they
are building a company for the long haul and are willing to invest their time
and energy into partnerships and clients.
obvious question will be price. Anyone willing to offer value-based solutions
will only do so with a paid pilot. Free or low-cost projects should raise
questions to whether the fintech even values its own service. It may be
tempting to say yes to ‘free’ but when have you accepted free services and
gotten long term value in that product?
- Data Quality and Security
the highly regulated nature of the financial industry, banks must ensure that
the fintech complies with relevant regulatory standards and possesses a robust
data security framework. As mentioned earlier, even the federal regulators are
vendor implement best practices for securely transferring data, validating
authentication and safeguarding from potential attacks?
does the data need to be compliant and secure, but reliable. Banks should seek
out partners who have a proven tenure in providing validated, and even
published, metrics to clients.
- Innovation and Future-Readiness
must also choose a fintech that is committed to continuous innovation and
adapting to emerging technologies. This ensures that the bank can stay ahead of
industry trends and market needs.
Ag lending offers tremendous opportunity for
banks, but it does require a unique set of skills and expertise. Fortunately,
agfintechs can fill these knowledge and data gaps. The challenge is
differentiating among the many partner choices. By considering these five
critical factors, banks can better evaluate partners and create a solid path
forward that generates greater profitability and helps solve a need within
Jim O’Brien, CEO of Agrograph
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