Abstract

Outlier detection is a very important concept in the data mining. It is useful in data analysis. Nowadays, a direct mapping can be found between the data outliers and real world anomalies. Hence the outlier detection techniques can be applied to detect the abnormal activities in the real world. Outlier detection has been researched within various application domains and knowledge disciplines. This survey provides an overview of existing outlier detection techniques that can be applied in the financial domain. It mainly focuses on the idea of detecting the suspicious or outlier financial transactions.

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