Credit Card Fraud Detection using Anomaly Detection

Fraud is a malicious activity that causes financial loss. Fraud causes by Credit Card have costs consumer as well as banks. Nowadays fraudsters are implementing diverse methods to commit frauds. So there should be a system like fraud detection which has the capability to detect the fraud activities before occurring and also in an accurate way. This paper discusses the utilization of machine learning methods in credit card fraud detection. Anomaly detection is a decisive obstacle that has been examined in varied research zones and various application domains. For a particular domain, different anomaly detection methodology has been specifically developed. This paper will talk about anomalies and its various types. Different aspects and challenges are considered in anomaly detection. Training data and different techniques are used in anomaly detection to solve a particular problem. Moreover it will discuss how the different techniques of anomaly detection are applied to solve the fraudulent activities in credit card data and what factors should be consider to apply to get full accuracy in the detection of fraudulent tasks in credit card data analysis.