Abstract
Modern services like e-commerce, which emerged from the technological revolution, are some of the many domains that greatly contributed to business thriving by reducing costs, saving time, and increasing productivity by enabling companies and individuals to execute their financial transactions electronically. However, the remarkable rise of financial transactions due to the massive adoption of internet bank services, FinTech innovation, and e-commerce has increased the risk of malicious attacks aiming to perform fraudulent activities. Data mining and artificial intelligence are approaches that have widely been used as fraud detection techniques. Researchers have taken advantage of such methods to discover abnormal activities through which fraudsters intend to violate the law. In this research, the authors first introduce different types of financial fraud in e-commerce systems, then review various data mining methods to deal with them. Finally, the most efficient techniques regarding different types of fraud that can be applied to detect anomalies have been identified.
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