Agrograph

Agrifinance for Investors: What you should know and why you should consider investing in agriculture

Data solutions are removing the long standing barrier of access to transparent and critical information, making investments in agriculture not only wise, but more approachable than ever.

by Scott Roberts

April 27, 2022

Typically, ag lending services have been reserved for banks with close proximity to such investments - the farm itself. A hindrance to portfolio diversification has long been the inability to physically review a farm seeking input or operational financing. But today, that’s changing.

While traditional banking is still practiced widely across the industry, technology is propelling alternative methods of providing service as customers come forward with an expectation for speed and convenience. The challenge for smaller institutions - meeting the demand and scaling to offer sufficient amenities like mobile banking and online lending.

However, organizations that have the human capital and infrastructure to promote such conveniences are in a prime position to expand into unique territories and investments like agricultural operations.

Agriculture serves as an alternative asset class. It is uncorrelated to other major asset classes such as equities and fixed-income and desirable due to its lack of volatility or correlation to the stock market. However, because of a notorious lack of transparency in the market, banks have avoided approaching the sector at scale.

Today, however, data solutions are removing the barrier of access to transparent and critical information.

Taking inspiration from innovations found in precision agriculture production, the technology used for driving tractors and determining application rates of fertilizers, the finance sector can realize new opportunities through Agrifinance by now leveraging physical farm data to drive financial decisions.

Common practices in agrifinance, such as anticipating default risk, assigning overall value to a portfolio, estimating cash rental rates and even determining volatility rely on impactful production metrics such as land value, historical crop production, weather patterns, and more.

The convergence of technology to agriculture and banking is great in concept, but it’s only useful for those with access to reliable data and validated models that account for risk factors. This is where the solutions offered by Agrograph are proven to improve processes while managing risk.

At Agrograph, we deliver multi-level data solutions designed to address the challenges associated with these modern agrifinance processes. Our software leverages satellite imagery and machine learning to generate visual tools that allow users to measure the metrics critical to not only providing, but improving upon their services.

We are the Credit Score of Agriculture™. Our featured Agros® Risk Score empowers financial institutions to assess the creditworthiness of agricultural operations, but our solutions’ benefits reach much further. With our other Agros® Scores, we answer the toughest questions facing the agricultural industry today. Our custom Agros® Reports take that data further, combining Agros® Scores and uniquely picked metrics to provide deeper insights.


Interested in learning more? Reach out to us.


Scott Roberts is an electrical engineer with a background in signal processing and machine learning. With over 2 decades of experience, he is well-versed in solving machine-learning problems from data infrastructure to the deployment of models in mission-critical production settings. He has an M.S.E.E. from Stanford University and a Ph.D. E.E. from the University of Illinois.

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