Anomaly detection is the process of finding outliers in the data set. Outliers are the data objects that stand out amongst other objects in the data set and do not conform to the normal behavior in a data set. Anomaly detection is a data mining application that combines multiple data mining tasks like classification, regression, and clustering. The target variable to be predicted is whether a transaction is an outlier or not. Since clustering tasks identify outliers as a cluster, distance-based and density-based clustering techniques can be used in anomaly detection tasks.