Machine Learning Approach to Predict Farmer’s Loan/Credit Repayability using Weather Prediction and Credit History

Abstract

The premise of our paper is with the help of Machine Learning, we aim to develop a comprehensive rating system using the predicted outcome of weather prediction and an individual's credit history. With our system, an individual could find out the likelihood of the ability of fulfilling the loan undertaken, similarly financial institutions can use the system to find out the likelihood of the credit being repaid and the individual's eligibility of the maximum credit. The demand of agriculture sector has increased due to large population in India. It has become essential to consider effective technologies in agriculture. Through our portal, the idea is to develop an algorithm via machine learning would give a rating on a scale (0-10), which would determine the eligibility of the farmer being able to fulfill the loan. Through our portal, we will try to inform farmer and banker what all changes in weather are taken place and climate of all the region. Our portal uses the past forecasted raw data of few year to predict the recent forecast.