The Best Data Visualization Tools for Ag Finance Risk Management

For ag finance professionals, there is an acute need for tools that fit the current modern landscape. Information can be difficult to procure and can even be out-of-date. As the world continues to move faster than ever before, the Harvard Business Review writes:

“the ability to create smart data visualizations…was a nice to have skill… That’s changed. Now visual communication is a must-have skill for managers,  because more and more often, it’s the only way to make sense of the work they do.”

Data visualization tools are used to derive clear and concise information from datasets that can be inefficient to extract in a business context. Financial professionals are made more adept to identify patterns through the strategic insights provided by visualization tools. This method of accessibility also makes it easier for institutions to share findings with executives, regulatory bodies, and investors.

Three Key Features to Look for in the Best Data Visualization Tools

1. Data Un-Siloing and Aggregation 

The aggregation and integration of information are one of the most valuable takeaways data acclimation tools have to offer. 

While visualization software primarily focuses on visual formats, for its use case within agriculture, the aggregation of data is another necessary form of functionality. This is especially true in an industry where important info is more often than not, dispersed, not readily accessible, and has the potential of being geographically specific. These automated tools have the ability to carry the heavy load of conducting data discovery on their own, giving professionals additional time that can be better spent elsewhere. 

The way the agriculture industry operates today means informed decision-making is constantly being obstructed by things like incorrect data or missing context.

Fintech that pairs data visualization and acclimation gives ag finance professionals the opportunity to assess their data and cross-reference with other relevant datasets. Bringing first- and third-party data together through secure APIs results in a thorough analysis that meets the modern standard for decision-making professionals. Reports are populated with up-to-date information and can be iterated as more timely findings are made. 

2. A Geospatial Aspect 

Risks in agriculture are geospatial.

In data management in ag finance, sifting through endless cells and columns within various Excel sheets can take hours, let alone counting the amount of time it takes to collect that data and input it. That’s not even the dedicated storage systems needed to house large quantities of data and the manual data entry that is traditionally required.

Ag lending portfolios can many times contain parcels and borrowers that are in different regions. Because of this, the portfolios are exposed to a complex combination of regional, borrower-specific, and sometimes regulation-driven external factors. Through the power of data visualization, ag lenders are able to visualize the full picture in a matter of minutes. 

To gain insights, data has to be not just analyzed, but presented in a way that makes that data work. Geographical context provides the visual connection necessary to seamlessly identify and monitor trends, as well as track allocation, wildfires, droughts, and other climate-related risks. All of these pieces work to make the decision-making process more time-efficient. 

3. Compatibility Features for Financial Institution’s Existing Risk Management Practices

One of the most important capabilities any data visualization tool used by ag finance can have is the ability to work on a case-by-case basis for institutions and pull reports on both parcels and entire portfolios. Products should be prioritized based on the level of internal disruption they pose to the business. Migrating to a new tool should be a process that is made as simple as possible. 

If the goal is to become more efficient, the tool should not actively slow down or hinder the financial institution’s goals.

For this reason, the integration capability of tools is an important factor for professionals to make note of. 

An important thing to consider is: How easily can existing data be transferred over to the new tool? If the decision comes down to just this question, one service which would require a complete overhaul of an institution’s data collection versus another can parse the data as is, the latter is the more sensible option. 

Standardization is also a caveat to the process of conducting research within the ag sector. This makes the process of risk analysis like trying to complete a puzzle with pieces from hundreds of different boxes. 

The Bottom Line

If financial institutions want to build or maintain a competitive advantage, they can invest in decision support solutions that will make them more agile in their loan decisioning process. This is a shift deriving from necessity; old methods can no longer be supported in a digital age where mammoth amounts of siloed data can be crucial to resilience planning for the future.

There are better ways to use data, and innovative tech is being used to improve agriculture worldwide. Legacy methods cannot support the standards that will be required by the industries of tomorrow, especially in agriculture.

Data visualization tools were created to deliver complicated analytics through interactive methods. AQUAOSO’s GIS Connect is a climate fintech solution specifically designed to use data visualization and provide Farm Credit with a robust application that efficiently delivers them a comprehensive overview of risk factors present in their portfolio.

Request a demo to see it in action or explore our Resources page to learn more about data visualization in agriculture.

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