AI-Driven Credit Scoring Model For Farmers:
Credit scoring for farmers is a lot more different and demanding when compared to credit scoring for financial institutions or businesses. Challenges are many due to the low level of financial inclusion of farmers and their limited access to credit. This is compounded by a lack of structured data and related information with respect to farmers. This project aims to address this problem by first identifying relevant data that can help in coming up with a roadmap for quantifying their credit risk. Subsequently, appropriate machine learning techniques will be utilized to come up with a credit scoring model for farmers. This study is also expected to provide insights on promoting financial inclusion for farmers.
AI-Driven Crop Selection: Agriculture is the heart of the Indian economy and depends on various external conditions. Providing farmers with digital solutions for their crops such that they can choose one of the best productive crops to grow while considering all factors such as climate, geography, etc. We are using cutting edge tools and Machine Learning techniques to build the model
Faculty Advisors: Prof. Usha Ananthakumar, SJSOM, IITBProf. Sauli Mukhopadhyay, Mathematics, IITB