The agriculture sector is constantly evolving as more and more new technological innovations are being introduced to bring about efficiency and enhance farm productivity. The modernisation of the diverse operations and the consequent increase in the cost of managing a farm is thus calling for increased investment in the sector. Notably, smallholder farmers are more so in need of credit that will enable them to purchase good quality seeds and the right farm equipment, take care of overall farm maintenance before the start of a season, and manage operational costs until the sale of harvested produce. Studies show that when farmers have adequate and timely access to finance to purchase quality inputs, they are able to increase their farm productivity up to 50%, which consequently improves their livelihood and helps bring them out of poverty. However, what are the factors that make rural lending a highly neglected area?
In recent decades, agriculture finance markets in India have been expanding to cater better to the millions of smallholder farmers. Nonetheless, banking and finance institutions that cater to agri-lending face a fair share of constraints including a higher incidence of NPAs, inadequate risk mitigation tools, high operational costs in servicing deeper rural geographies, lack of reliable or alternate data to assess farmer’s credit-worthiness, the right instruments to monitor the usage of the credit, and the business itself being high-cost and low-margin.
NPAs and delinquencies are on the rise for over five years primarily as an outcome of falling farmer revenue across the country. The central and state governments, in their efforts to alleviate farmer distress, waive or write off farmer loans every now and then, which further adds to the lending institution’s reluctance to cater to smallholder farmers. This uncertainty around the credit-worthiness of farmers can, however, be overcome when lenders have access to the right data, and the right quality of agri-data, which helps make the entire process efficient and cost-effective.
Banks and other financial institutions are increasingly leveraging agricultural technology to arrive at sound, data-driven lending decisions that help optimise their services for the rural agri-community. A recent panel discussion at the Agri-Innovation Summit 2019 hosted jointly by CropIn Technology and The Economic Times invited distinguished industry leaders to share their opinions on how the next generation AgriTech is enabling better access to finance and insurance for smallholder farmers. According to Sumit Gupta, Senior Group President of Yes Bank, ensuring the delivery of farmer subsidies and payouts directly to the farmer’s account is now easily possible thanks to digitally-opened accounts linked to Aadhar and a whole lot of other benefits. Banks are adapting the various processes to technological disruption, including the delivery of credit and micro-credit to people in rural regions using a large network of business correspondents, to try and make sure that the time taken for the delivery is as less as it gets and is done straight to their account.
As the Chief Business Officer at Samunnati Agro Solutions, Suresh Devnani remarks that the solution for some challenges are not loans, but intervention through market linkages or trade solutions, and that is where Samunnati Agro solutions play an integral role. “We have been fortunate to associate with CropIn in areas where we have been doing some work with FPOs. Many would have experienced how difficult it is to get certain records from the FPOs as it takes weeks to maintain those records and to analyse it is even more difficult. When we work with Cropin, all the records are digitised and we have recognised the advantages that come with the digitisation of all records.” The digitisation also brings efficiencies into the system by delivering data similarities, which can make financing for banks more efficient and accessible.
Shripad Jadhav, who heads agribusiness retail at Kotak Mahindra Bank, reveals that in the last 3-5 years, following the increase in mobile penetration in India, bankers are using technology for customer acquisition, credit underwriting, monitoring end usage of credit, and for the management of receivables. The advantage of technology is that it does not dilute, it does not collude, and it does not pollute data. Moreover, data collection from rural regions is now more credible, and demand minimum time and effort as compared to traditional processes. This accuracy and reliability of farm and farmer data enable lenders to establish whether the farmer will be a good ‘asset’ to the bank or not.
He further adds that statistical models built using satellite image processing and machine learning enable lenders to forecast what the farmer’s yield would be and the potential risks involved, along with examining the various risk mitigation options for both the banker and the farmer. AI-powered platforms such as CropIn’s SmartRisk® empower banks to establish the agri credit-worthiness score based on a combination of various data points including what was historically grown by the farmer, the potential that exists in the region. Image processing and big data analytics also facilitate financial institutions to remotely monitor farms performance and the crop’s health in real-time. If required, banks can also provide remedial advice to farmers to ensure a successful harvest. This not only enables farmers to repay loans on time but also improves their credit history for future transactions.
One of the most important factors that enable faster adoption of technology is behavioural change. More often than not, financial aid in the form of Kisan Credit Card (KCC) or other government schemes is almost always withdrawn in the form of cash. This leaves behind no trail of how the funds were used, which proves to be a mighty challenge when lenders need to analyse a farmer’s expenses to provide credit that suits the requirements better the next time. It thus becomes paramount to make transactions transparent by implementation policies that drive digitisation and bring about change in people’s behaviour, towards more cashless digital transactions even in the more remotely located regions.
From a Government of Odisha to a renowned financial institution in Australia, technological interventions have enabled numerous lending organisations to invest more in farming communities. These organisations are now able to establish better relationships with smallholder farmers with the use of credible data and provide service that adds value to both banks and farmers.