Impact of Imbalance Data on ML Model: Fraud Transaction Case

Imagine standing at the check-out counter at the grocery store with a long line behind you, and the cashier not-so-quietly announces that your card has been declined. Embarrassed, and certain you have the funds to cover everything needed for an epic nacho party for 50 of your closest friends, you try your card again. As you step aside and allow the cashier to tend to the next customer, you receive a text message from your bank. "Press 1 if you tried to spend $500 on cheddar cheese." This is an example of a fraud transaction scenario in real life happens.