Business Analytics and Business Intelligence Machine Learning Model to Predict Bank Loan Defaults

Pages: 72

Language: English

Published on: May 29, 2020

Publisher: Idea Publishing

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Predictive Analytics offers a unique opportunity to identify future trends and allows organizations to act upon them. In this book we are dealing with ‘loan default’ which is always a threat to banks and financial institutions and should be predicted in advance based on various features of the borrowers or applicants.In this book we aim at applying machine learning models to classify the borrowers with and without loan default from a group of predicting variables and evaluate their performance.

As a part of building a model to predict loan default, we have submitted in detail the introduction of the problem, exploratory data analysis (EDA), data cleaning and pre-processing, model building, interpretation, model tuning, model validation, and final interpretation & recommendations.

Under the current project of loan default forming part of predictive analytics of business analytics and intelligence, we have studied research-based review parameters in detail which have also been annexed for ready reference as Annexure I. Data dictionary has been annexed as Annexure-2. R. Code for the same is provided at the URL which can be downloaded from

The study finds out that logistic regression is the best model to classify those applicants with loan default.