Anomaly detection system in credit card transaction dataset

Over the past ten years, network and technological connections have improved, and more users now regularly use the internet. Thanks to users, the population using online payment methods is constantly expanding since they are simple, easy to use, and convenient. Credit card theft arising from system abuse is the term used when information from a credit card is taken or used without the cardholder’s permission and when it isn’t done for the cardholder’s personal gain. In order to spot such, it is crucial to look at the consumption trends throughout a user’s prior transactions. A credit card anomaly is the actual loss of a credit card or the actual loss of personal credit card information. Many methods based on machine learning are utilised for detection. The XGBOOST Classifier should be the most effective model for this issue. For binary situations like these, it is one of the quick detection algorithms.