Antifraud Hub

Related Articles

• Antifraud articles

  This collection maps the core techniques, signals, and control points behind antifraud work. It covers device and browser fingerprinting, IP and email checks, rule engines, case management, and detection patterns for account takeover, synthetic identity fraud, merchant fraud, and bot activity.

• Event-Driven Antifraud in eCommerce

  Event-driven antifraud in eCommerce starts with a simple idea: collect the right events, then make fraud decisions based on what the data shows. This article covers bot prevention at the infrastructure layer, behavioral analytics, and the event signals a rule engine can use to flag suspicious purchases before they go through.

• Advanced Fraud Rule Engines: Complex Policies and Third-Party Data

  Fraud prevention is no longer a single check. It depends on a fraud rule engine that enriches data from multiple sources, applies clear knockout rules, and combines scoring with decision logic in real time. This article explains how complex policies, third-party data, behavioral signals, and machine learning fit together in a practical antifraud setup.

• Why Case Management Matters in Anti-Fraud Work

  Fraud teams need more than detection. They need decision logic, case tracking, and a clear path from alert to resolution. This article explains why case management matters in anti-fraud work, which functions it should support, and how automation removes repetitive tasks without reducing control over the investigation.

• Media Device Fingerprinting: A Modern Method for Online Tracking

  Media Device Fingerprinting uses browser APIs to collect details about a user’s audio and video devices and turn that data into a tracking signal. This article explains how it works, why it matters for online fingerprinting, where it falls short, and what can reduce its effectiveness.