The objective of this exercise is to understand which parameters play an important role in determining whether a client will default on the loan payment or not.
First Step: Load the dataset
Second step: Data Preprocessing.
Third Step: Feature Engineering.
Fourth Step: Model building using CatBoost Classifier.
Fifth step: Evaluate the model.
The metric score used is the percentage of all correct predictions made. This is simply known as accuracy.