Introduction

In the previous chapter, we analyzed online shoppers' purchasing intent and derived various useful insights from our findings. We explored and utilized the K-means clustering technique, along with univariate and bivariate analysis, and also studied the linear relationships between each feature of the dataset to build a proper evaluation of the dataset. The results derived from the analysis would help a business to identify the pain points and develop new business strategies to tackle them.

In this chapter, we will analyze credit card payments of customers and use their transactional data to study the characteristics of the customers who are most likely to default, eventually building a profile of these customers.

Credit card default has been a field of interest and extensive analysis for more than a decade. There are two types of loan – secured and unsecured. A secured loan is one where some collateral is mandatory, so whenever a default happens, the...