"Buy now, pay later" is a tempting offer in today's consumer-driven world. It allows us to satisfy our immediate desires without having the money upfront. However, this impulsive behavior often leads to mounting debt and financial distress, potentially pushing individuals into default or even fraudulent practices.

We can tackle this problem using machine learning. By analyzing a buyer's financial history, we can assess their creditworthiness. While we can't control companies' marketing tactics, we can proactively evaluate individuals' financial backgrounds to make informed decisions about lending or offering credit.

The primary objective of this project is to leverage machine learning to predict whether a credit card user is likely to default on their payments. By evaluating past financial behaviors and patterns, we aim to provide credit decisions that are both responsible and sustainabl.