In India, agriculture is an important mode of employment as more than 50% of the population do farming. The risks associated with the agriculture industry specifically in India are aggravated by various factors, ranging from climatic variability, frequent natural disasters, uncertainty in production yield and market prices, lack of proper rural infrastructure, imperfect market and financial systems including the inefficiency of risk mitigation instruments like credit and insurance. The above-mentioned factors not only possess imperil risk to the livelihood and income of the farmers but also hinder the whole agriculture sector to become part of the solution to the problem of prevalent poverty of the farmers and the agricultural labor.
The major problems lie in the complexity of agriculture sector in terms of farms size, mixed crop plantation, drastic climatic changes etc which has led to disengagement of the banks and other financial institutions to engage in rural finance. The remoteness of the rural clients and poor financial networks increases the cost of doing business in these types of areas. The risks associated with the agriculture lending and earning higher profits is very high and unmanageable due to lack of sustainable infrastructure and solutions. India’s rural transformations and national economy are dependent on the agriculture for which fiscal and monetary interventions are required to ensure the securities of farming community but also to generate constant mode of income, savings, and investment. The grossly underfunded agriculture sector provides huge opportunities for the insurance and reinsurance companies to provide sustainable solutions to the farming individuals by providing the necessary capital to come out of poverty trap and get insulated from the income shocks.
In last 10 years, the lot of technologies advances happened in satellite data, artificial intelligence and big data cloud computing that has disrupted the technologies in a positive manner for the real-time large area monitoring. Geospatial domain has the ability to provide a viable solution to the government and financial institution to efficiently assess, mitigate and cope with the all kind of risk that agriculture sector possesses. Due to the availability of the satellite data from late 1990 until now, it helps in better assessment of risks, its consequences, and prioritization. The risk-mitigating and transfer strategies can be dominated by the geospatial domain which can be used to generate real-time info, early warning signals and large area monitoring in terms of vulnerability and crop suitability mapping, production data prediction, and natural disaster signals etc. to provide intervention insights to the farmers, government and other financial institutions. Also, it is very useful in implementing risk coping strategies by objectively triggering signals for the impending disaster for a large area scalability of social safety net programs.
The agriculture credit risks can be defined in terms of farmer’s ability to repay loans. Most of the farmers in India do not have a bank account and tend to depend on non-institutional sources like local money lenders. These local money lenders thrive on high risks and charge high-interest rates. One of the important reform that took place in 1969 was bank nationalization to increase the availability of the credit to agriculture and free farmers from the holdings of the private money lenders. Banks were advised to allocate lending resources in the rural areas for the purpose of increasing the credits in the rural agriculture sector which led to an expansion of banking branch network in the rural areas. Even after expansion of the banking network in the rural areas most of the farmers are not able to obtain capital help from the banks or insurance companies. The major reason for the failure of the system is due to lack of credit history of farmers in terms of income generated in the past. The geospatial technology and big data analytics will play a vital role by going back in time to assess the agriculture profile of the farmers to give indications to the bank of the loan repaying ability of the farmer. It will also enhance the agriculture insurance from the index based on more localized insurance model to better assist farmers in the catastrophic situations. It will also help government better design the risk management policies that can be effective on a large scale.