Machine Learning Based Model for Prediction of Loan Approval

Abstract

Banks are vital to financial management and controlling the economy of a country. Banks and financial institution distribute loans and these loans act as the core business part of almost every banks. The profits are earned from the loans distributed by the banks. The prime goal is to invest their assets in safe hands. The success of bank depends on the decision-making capability to evaluate risk of lending loan to the customer. Checking manually individual consumer’s credibility for the loan approval is difficult, time consuming and risky. Thus, the banks aim to minimize the credit risks of defaulting. In this study we have applied logistic regression as a tool to predict whether an applicant is eligible for the loan or not. The data is collected from the Kaggle for studying and prediction.

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