Machine Learning Methods for Detecting Fraud in Online Marketplaces

by ProductDock 03/17/2022

Securing a safe environment for buyers and sellers is the burden of online marketplaces, since their reputations attract many malicious users who are likely to abuse the platform for personal monetary gains. Fraud detection and prevention of malicious actions hence represent a real challenge, where platforms have to respond adequately, and in a timely manner.

Several teams at ProductDock currently work for the world famous eCommerce platforms in Europe, North America, and Australia.

Raoul Dekou PhD Data Scientist at mobile.de and the writing team of co-authors: Savo Sabljic (ProductDock*), Francesca Diana (codecentric AG), Simon Kufeld and Ricardo Kawase
(Inovex GmbH) have recently published their scientific article: Machine Learning Methods for Detecting Fraud in Online Marketplaces. The paper was published in the CEUR Workshop Proceedings**.

 

*ProductDock is a subsidiary of codecentric AG.
**CEURWS.org is a free open-space publication service at Sun SITE Central Europe operated under the umbrella of RWTH Aachen University.