This is a Business problem span accross the world and its a major issue globally. Its has made Financial institution go bankcrupt as a case of 2008 in the USA.Bank and other Financial institution provide funds for potential borrowers and in reture earn a profit depending on the risk they take (the borrowers credit score). They provides loan to their loyal customers. The purpose of this work is to combine Machine learning Intution across customer available data such as credit score gotten from a reliable organisation. This dataset is gotten from Kaggle and its for learning purposes. I dont have any intention for Plagiarism any data.
There are over 100,000 data available for analysis. Two algorithm will be used for evaluation, Logistic Regression and Random Forest classifier. we will select one that best suit the given data which will be evaluated based on their AUC score
AUC(Area under curve) score represents degree or measure of separability. It tells how much model is capable of distinguishing between classes. Higher the AUC, better the model is at predicting 0s as 0s and 1s as 1s or probabiity. The reason for predicting probability is to give the company a range of score for each customer which will be use for Risk Management