LOAN STATUS PREDICTION SYSTEM

Abstract

Banks are making major part of profits through loans. Though lot of people are applying for loans. It’s hard to select 
the genuine applicant, who will repay the loan. While doing the process manually, lot of misconception may happen to 
select the genuine applicant. Therefore we are developing loan prediction system using machine learning. Leveraging 
a rich dataset encompassing historical loan records, the model incorporates crucial applicant features such as credit
score, income, and employment history. Various machine learning algorithms, including logistic regression and 
decision trees, are employed and compared to optimize predictive accuracy. Our system aims to enhance lending
institutions' decision-making processes by providing a reliable tool for forecasting loan outcomes. Through rigorous 
evaluation and validation, our developed model demonstrates predicting loan approval or rejection.