Agricultural Loan Recommender System - A Machine Learning Approach

Abstract

Agricultural loans provide a much-needed support structure for the overall functioning of the agricultural industry in a country like India where a majority of farmland is owned by a multitude of people, which leads to scattered ownership of the overall farmland and in turn restricts the potential growth of the agricultural industry. This leads to the need for a proper system to improve the efficiency of loan acquisition on the farmer's end and loan supply on the bank's end. In this paper, a feasible Agricultural Loan Recommender system is presented using K- nearest neighbour algorithm. It enables the farmers to look up statistical and graphical data relevant to agricultural loans and to get recommendations for said loans. Using this system can help farmers be better informed on the overall process of the loan application as well as which bank would be the most suitable to apply for a loan based on their needs. The results of the scheme are analysed with respect to the probability of bank recommendation based on the requested loan amount.