Loan Eligibility Prediction using Machine Learning

Abstract

The Loan Eligibility Prediction project utilizes machine learning to assess an applicant's eligibility for a loan based on key financial and demographic factors, achieving an accuracy of 85%. The model is trained on historical loan data, incorporating features such as income, credit history, loan amount, and employment status to predict approval likelihood. A web interface built using HTML, CSS, and Flask allows users to input their details and receive instant eligibility results. This system enhances efficiency for financial institutions by automating decision-making, reducing processing time, and minimizing human bias in loan approvals.