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eCommerce Fraud: How Fraudsters Use the Dark Web To ‘Warm Up the Shop’ and Fool Rules-Based Anti-Fraud Systems


Imitation is never perfect. The perfect solution to prevent a successful ‘warm up’ attempt comes in the form of truly knowing your users (KYU) and understanding their interactions and behaviors. Advanced fraud solutions powered by machine learning models can effectively weed out fraudsters before they’ve had a chance to warm up. Watch Mateusz Chrobok, R&D of Nethone, to discover how.

Vector-3 23 June 2022
Mateusz Chrobok

R&D Advisor, Nethone

Mateusz Chrobok, Nethone’s new R&D Advisor is an expert of Cybersecurity, AI, and Startups. Besides being the technical founder of Digital Fingerprints, Mateusz spent the last two years within Buguroo (later acquired by Feedzai) as a VP of Innovation, responsible for their passive behavioral biometrics. Also, he has 5+ years of experience in R&D for Samsung with multiple successful projects around the World.

Learning objectives:

  • Understand the long process of fraudsters ‘warming up the shop’ to bypass rules-based anti-fraud systems by acting as naturally as a regular customer as possible.

  • Be aware of the tools and knowledge available on the dark web that allow fraudsters to fool rule-based fraud systems.

  • How KYU Advanced fraud solutions powered by machine learning (ML) models can help you understand every user behaviour and interaction - and prevent fraud from happening.

Learn how to spot the behavioral signals of fraud attempts