Satellite-based Remote Monitoring And Analytics For Making Grounded Farm Loan Decisions

Satellite-based Remote Monitoring And Analytics For Making Grounded Farm Loan Decisions

EOS Data Analytics introduces satellite-based field monitoring to help agri banks in loan risk assessment

Access to capital within farm loan programs is crucial for agricultural entrepreneurs worldwide, especially those managing small (up to 10 hectares) land areas. These funds could be used for modernizing farm operations: purchasing new machinery, testing more effective inputs, or adopting software to gain more control over farm management.

Before deciding whether or not an agricultural entrepreneur is eligible for a loan, banks must assess documentation and statistics about farm productivity performance. A variety of records can bring one context to operations: historical yields, current and historical agrometeorological conditions in an area of interest, income and expense records from previous seasons, daily activity and input logs, latest data on the state of crops and soil on the farm territory, and more. And if a potential client hasn’t provided enough information on a farm’s profitability and productivity, an agricultural lender can send scouts to check fields and fill data gaps.

Evaluating documentation usually takes dozens of person-hours, while farm inspections could cost a significant part of the credit amount itself (if we’re dealing with loans for small-scale farmers). Nevertheless, financial institutions never skip loan assessment as they aim to avoid two primary risks:

  • Inaccurate or inconsistent records about farm operations
  • False documents about farm performance and profitability in question

Agricultural banks can partially automate and streamline data collection and verification for loan risk assessment by using satellite-based software for remote monitoring of farmlands. EOSDA Crop Monitoring by EOS Data Analytics is one such solution.

“EOSDA’s precision agriculture platform provides centralized access to data from multiple sources, including optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) satellites, ground sensors for soil moisture, and weather stations from two providers — World Weather Online and Meteomatics. Relying on this data, financial institutions can understand the past farm performance and even estimate their yielding ability in the current and future seasons to make informed loan decisions,” notes Brijesh Thoppil, Strategic Partnerships Lead at EOS Data Analytics.

Moreover, the platform will soon start sourcing data from EOS SAT — the first agri-focused constellation among remote sensing companies. After the launch, the company will manage the data cycle in-house, from acquiring and processing satellite data to deriving insights from it.

Recently, EOSDA hosted a webinar about the technical capabilities of the EOS SAT and how customers can use it for their benefit. Feel free to watch it to learn more.

Briefly about the EOS SAT constellation powered by EOSDA. Video: EOS Data Analytics

The platform is powered by machine and deep learning algorithms, allowing it to process and analyze multiple data points, providing users with analytics on crop development, growth, and soil condition.

The following features will be useful for bankers:

  • Field leaderboard — sorting fields by critical change in NDVI (Normalized Difference Vegetation Index) values, crop type, location, area, by crop type, location, area, group, image date, and group;
  • Historical crop rotation data starting 2016 — information on what crop types were cultivated in the same field over several growing seasons;
  • Historical weather data since 2008;
  • Field productivity data starting 2016;
  • Soil moisture data (the amount of water in the soil against the whole soil volume) since 2015. Data is available for the U.S., Nigeria, Ukraine, Kazakhstan, Brazil, Canada, Australia, and Argentina. Soil moisture data can be developed for other countries on demand.

EOSDA can implement custom yield forecasting projects if necessary.

Getting EOSDA Crop Monitoring for financial institutions

Financial institutions can consider two partnership options:

  • Using EOSDA Crop Monitoring under a subscription. A basic user plan comes with 5000 ha for monitoring. A bank can start using the platform right away after registering their account.
  • Building a white-label solution by adapting the look and feel of the EOSDA Crop Monitoring interface to the company’s branding and handpicking features
  • . There are two white-label options that differ in the number of services and customization levels: Basic (includes the platform’s desktop version) and Advanced (clients get a scouting app and a clientele management tab). Companies that decide to bring a white-label solution to market join the EOS Data Analytics Partner Program. The program allows an agricultural bank to give customers access to the precision farming tool. A financial institution can also use EOSDA’s marketing resources to make customers and prospects aware of its services.

Depending on the option (Basic or Advanced) and requirements, clients can get ready-to-use software in one and a half to three months. On the contrary, custom software development may take up to one year.

Regardless of a preferred partnership type, banks that integrate satellite imagery analytics into their operations will be able to:

  • Assess loan risks faster
  • Minimize credit default risk by having information about farm performance
  • Expedite loan processing and optimize overall workflow
  • Avoid unnecessary field inspections
  • Implement custom projects, such as yield forecasting and crop classification

EOS Data Analytics strives to support farm loan program applicants and lenders by providing satellite analytics solutions. Eventually, speeding up farm loan application assessments might contribute to thriving agriculture dynamic growth of banking sectors: Agricultural entrepreneurs will access financing to maintain, modernize, or enlarge their farms, while financial institutions will increase earnings by making more deals in a given period.

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The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of The World Financial Review.