Disrupt a ready-to-harvest ecosystem with automation

* With the automation of processes and the digitization of many data points involved in the crop lending operation, the segment is a gigantic big data game.

* There is an urgent need to adopt modern financial technology in crop lending

* Banks should view crop loans as a tremendous business opportunity and not as a necessary evil push from the government.

In the absence of available data, disbursing loans to farmers through Kisan credit cards becomes a difficult task for banks, resulting in delays and even loan refusals, sometimes leading farmers to borrow on unfavorable terms. from lenders.

Crop loans are essential for millions of farmers – especially those in the small and marginal categories. The Center provides grants of up to 3 lakh, and with an added incentive for timely repayment, the effective interest rate reaches an affordable rate of 4 percent. Banks have been mandated to guarantee crop insurance coverage for farmers at a negligible premium.

Despite affordable agricultural loans, only about 60 percent of the country’s farmers have had access to institutional credit. Crop credit processes in banks are largely controlled without any automation.

Farmers traditionally lack close relationships and engagement with credit institutions and banks. Indirect costs discourage him – waste of time in collecting documents, traveling to branches, expenses incurred for verifying land ownership documents and processing fees by banks. Farmers in desperation have also been taken advantage of by people posing as bank representatives or agents on numerous occasions.

The question of subsidies

Subsidies and waivers are another set of issues that banks face. These waivers are used like a carrot to collect votes. But these strategies cause constant damage as they impact loan repayments and increase non-performing assets (NPAs). In 2016, waivers crossed the ₹ 2.4 trillion mark. In 2019, loan default was over 11%. But there is no denying that subsidized agricultural loans are the need of the hour for farmers.

However, there are significant issues as to who is actually eligible for a loan. Limited data to qualify a farmer for the loan and a lack of real-time engagement with farmers on crop success, challenges and risks are important factors in determining yields. There are several challenges in accurately and robustly predicting loan performance.

Role of data

Current farmers’ reimbursement solutions treat the symptoms, not the problem – and that is poor crop performance. There are issues with all kinds of exclusions. Correct diagnosis and mitigation of these problems is only possible through authentic and credible data collection and analysis.

All banks are required to provide 8% loans to smallholders and marginal farmers. With the current lack of digitization, it is difficult to collect the data points that provide a window into these metrics and it becomes difficult to track actual progress. It calls on banks and financial institutions to change their outlook and approach and adapt disruptive technological ideas to make bank lending work for the entire ecosystem of farmers, banks and government. This will lead to transparency and a strong loan system.

Need for simplicity, transparency

It is necessary to define criteria for offering crop loans – the area cultivated according to agricultural loans, seasonality of crops, availability and methodology of irrigation and several other parameters. However, it is also necessary to make this process hassle-free and extremely simple and transparent. This can be achieved by digitizing the process.

To create a healthy credit ecosystem, banks must view crop loans as a great business opportunity, not a forced government push. With the automation of processes and the digitization of many data points involved in crop lending operations, the segment is a gigantic big data game.

Digitization, the key

Handling this big data manually during crop lending processes leads to inefficiencies, delays, bias, lack of transparency – and even exclusions. Moreover, in the absence of digitalization, banks, governments and other stakeholders are deprived of the power of data analysis to make informed decisions on policies, products, processes, cross-selling opportunities. , etc. Therefore, there is an urgent need to adopt modern financial technology in crop lending.

Despite all this, there are risks associated with agricultural and agricultural loans which can manifest themselves as natural hazards or plagues causing distress for the banks or the farmer. Banks do not have very structured risk assessment models, and although they do, they are sometimes overlooked.

Risk assessment

Just like there is KYC, there is a need to evolve specific risk assessment models and generate a credit score – (Farmer Rating Score) and just like the KYC can be updated and shared with the farmer and, with the consent of the farmer, may be available at the bank. This will result in an equitable distribution of the loan and mitigate the risks for the bank.

Digitization can not only create transparency in the system by providing access to healthy credit and ending reliance on waivers, thus creating a strong system of crop lending, but also help banks target the market centric. farmers who can help them make a profit.

The author is CEO, Knowledge Network Solutions