Satellite imagery analytics at agricultural banks’ service

EOS Data Analytics introduces satellite monitoring solutions to aid farm banks in loan risk assessment

Satellite imagery analytics tools for remote monitoring of farmlands provide critical information on the crops state, which can be used to measure farms’ productivity and, therefore, farmers’ ability to repay. 

Agricultural growth is one of the most feasible ways to end extreme poverty, support households, especially in developing countries, and feed an ever-growing world population that is expected to reach 8 billion in 2022 and 9.7 billion by 2050. According to the World Bank report, developing the sector is two to four times more effective in increasing incomes among the poorest compared to other industries.

Access to credit within farm loan programs is one of the measures for stimulating sector growth: Farmers are always motivated to maximize the productivity and profitability of their lands as their well-being depends on it. However, they may not have enough savings to purchase newer machinery, purchase inputs or seeds, or adopt tech that is meant to help optimize farm management. For some, obtaining agricultural credit is the only opportunity to expand or innovate farm economies. 

In turn, financial institutions must ensure that producers of agricultural products are eligible to obtain loans to minimize credit default risk. In other words, lenders need to evaluate whether or not potential borrowers could harvest enough to meet their needs and fully repay credit funds. Assessment of farm profitability and cropping power generally includes checking documentation about farm management and revenue history and making on-site field inspections if the information isn’t sufficient. Reviewing and verifying documentation takes much time, and the cost of visiting farms could make up a significant part of the loan size itself (if we’re talking about credits for smallholder farmers). Despite it, banks invest their time and money in conducting loan application-related checks because they want to avoid two main risks:

• Inaccurate records about farm activities
• False documents about crop yields and farm profit

Luckily, adopting modern technologies can permit farm banks to step away from conventional approaches to data collection and verification for loan risk assessment.

Satellite crop monitoring for agricultural financing. Image: EOS Data Analytics

“Field monitoring based on satellite imagery analytics, along with the analysis of current and historical agronomic, weather, and soil moisture data, can help loan issuers understand the past performance of a farm in question and even estimate its yields in the current and future growing seasons to make an informed decision. EOS Data Analytics’ primary tool, EOSDA Crop Monitoring, connects the dots to provide a 360° view on farm operations, thus reducing banks’ workload,” says Brijesh Thoppil, Strategic Partnerships Lead at EOS Data Analytics.

EOSDA Crop Monitoring’s features bankers can use to support loan risk assessment

The platform is powered by machine and deep learning algorithms to process and interpret multiple data points and provide users with analytics on crops’ vegetation and soil conditions. 

Users can quickly get essential farm information using the field leaderboard — the feature of sorting farmlands based on the latest significant NDVI (Normalized Difference Vegetation Index) changes. It’s possible to group fields by crop type, location, area, group, image date, current index value, and the value change.  

Historical crop rotation data since 2016 — information on crop types grown in the same field over several seasons — will also come in handy. Users can access sowing dates, weather data, and vegetation index values about the area of interest. Since crop rotation is crucial for maintaining soil health, banks can use it to evaluate the farm’s productivity potential.

EOSDA Crop Monitoring is also a source of historical weather and field productivity data. Besides, the platform contains soil moisture data (based on the ratio between water volume in the soil and the whole soil volume) since 2015 for Ukraine, Kazakhstan, Brazil, Canada, Australia, the U.S., Argentina, Nigeria, and Russia. 

Using the data mentioned above, banks can forecast yields and rely on the prediction results when deciding whether or not to provide financing and what amount of money to lend. The company can carry out custom yield forecasting projects if needed. 

How to get started with EOSDA Crop Monitoring for loan risk assessment

Agri-banks have two partnership options to choose from:

• Subscription to EOSDA Crop Monitoring starting from the package for monitoring 5,000 ha
• Development of a white label platform based on EOSDA Crop Monitoring ready to resell to clients. Depending on the customization level and the number of services, Basic and Advanced white label options are available. 

Regardless of the chosen option, insights from EOSDA Crop Monitoring will help financial institutions to:

• Spend less time and money on loan processing by avoiding farm visits (scouting)
• Have a bird’s eye view of current and past activities on a farm that potentially influence yields
• Cross-check information from documents on farm management and performance
• Justify loan decisions with statistics 
• Implement custom yield prediction and crop classification projects 

EOS Data Analytics is eager to make running and participating in government and commercial farm loan programs across the globe smoother by providing satellite analytics solutions. In the end, streamlining farm loan application reviews might contribute to thriving agriculture dynamic growth of banking sectors: Farmers will access financing to maintain, better equip, or enlarge their farms, while banks will increase earnings by being able to seal more deals in a given period.