Loan Prediction Using Logistic Regression in Machine Learning

Abstract

For several problems, the banking industry still wants a more scrutinized predictivemodelling framework. For the banking industry, forecasting credit defaulters is a daunting challenge. One of the quality measures of the loan is the loan status, it doesn’t show everything immediately, butit is the first step of the loan lending process. The loan status is used for creating s credit scoring model. In order to identify defaulters’, end valid clients, the credit scoring model is used for reliable review of credit data. This paper's target is to build a credit scoring model for credit data. In order to develop the financial credit scoring model, various machine learning methods are used. We propose a machine learning classifier-based analysis model for credit data in this paper. We use the Min-Max normalization and Linear Regression combination. Using the program package Jupyter notebook, the target is implemented. This recommended model offers the best precision of critical details. In commercial banks, it is used to forecast the loan status using machine learning classifier.