Fraud detection and prevention in e-commerce: A systematic literature review

Abstract

The high volume of money involved in e-commerce transactions draws the attention of fraudsters, which makes fraud prevention and detection techniques of high importance. Current surveys and reviews on fraud systems focuses mainly on financial-specific domains or general areas, leaving e-commerce aside. In this context, this article presents a systematic literature review on fraud detection and prevention for e-commerce systems. Our methodology involved searching for articles published in the last six years into four different literature databases. The search of articles employs a search string composed of the following keywords: purchase, buy, transactions, fraud prevention, fraud detection, e-commerce, web commerce, online store, real-time, and stream. We apply six filtering criteria to remove irrelevant articles. The methodology resulted in 64 articles, which we carefully analyzed to answer five research questions. Our contribution appears in the updated perception of fraud types, computational methods for fraud detection and prevention, as well as the employed domains. To the best of our knowledge, this is the first survey on combining prevention and detection of e-commerce frauds, linking also architectural insights, artificial intelligence methods, and open challenges and gaps in the research area. The study main findings demonstrate that from 64 articles, only five focus on the fraud prevention problem, and credit card fraud is the most explored fraud type. In addition, current literature lacks studies that propose strategies for detecting fraudsters and automated bots in real-time.