Credit Card Fraud Detection Using Machine Learning

A credit card is a credit payment facility provided by banks or similar financial organizations that allow the card holders to borrow money to pay for products and services from merchants accepting credit cards. Since everything is now done electronically, there is a risk of card misuse and loss of funds for account holders. It is essential that the credit card companies should be able to recognize fraudulent credit card transactions so that the customers are not charged for products which they did not purchase. These types of problems can be solved using data science and machine learning techniques. This can be done by modeling the dataset using machine learning algorithms combined with credit card fraud detection. The essential key to machine learning algorithms can be the historical credit card transactions with data of those found to be fraudulent. The first step is to evaluate and pre-process the data before feeding the machine learning algorithm to the credit card dataset to determine algorithm parameters and calculate performance metrics. The pattern can be then used to detect whether a new transaction is legitimate or not. The goal is to determine the occurrence of fraudulent transaction.