Detecting the Credit Card Fraud by applying the Random Forest Algorithm

Abstract

Abstract- Credit Card is universally accepted both offline and online. With credit card one can make cashless purchases. Making transactions for money and other things is now easy, convenient, and commonplace. The number of credit card thefts increases along with technological advancements. Financial fraud has a huge compounding effect in the worldwide statement enhancement. The economy has suffered billion-dollar losses due to these frauds. These transactions are carried out so deftly that they appear authentic. Fundamental design methods and other simple approaches won't be able to function as a result. In order to decrease confusion and promote order, all banks now require a fraud detection method which is well-organized. In this study, machine learning is used to identify Master Card fraud. In order to enhance the most effective response to fraud detection issues, the Random Forest Algorithm and OD approaches are also utilized. It is still shown to reduce false alarms and improve fraud detection. The collection of data of credit card transactions has been made since 284,807 communications have been made by European cardholders. To recognize and stop the scam, some of these techniques might be applied to the credit card scam detection system of the bank.