Paper Title
Loan Prediction Using Logistic Regression

Today, the risks of betting on bank credit are different for banks and borrowers. The bank credit risk check must understand the risk and degree of danger. Banks must separate their customers to upgrade their capabilities so that they can explicitly zero out these customers. Banks must take customer nuances into account to automate capacity development measures; for example, gender, marital status, age, occupation, income, commitment, etc. are given in your online application structure. With the rapid increase in the number of transactions in the financial sector and the opening of a large amount of data, it can help customers to split direct transactions and reduce the risk of prepayment. Therefore, the basic expectation is the type of credit and it depends entirely on the bank's data. Keywords - Loan , Bank , Logistic Regression , Client.