Antifraud Hub

Related Articles

• 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.

• Private State Tokens in Online Antifraud: What They Change and Where They Fit

  Private State Tokens are a privacy-preserving signal for online trust. They can help separate real users from automated abuse and do not rely on traditional fingerprinting, which is getting harder to use as browsers tighten privacy controls.

• Protect Your Lending App with Device Fingerprinting, App Behavioral Data, and Face Recognition

  Fraud and identity theft target lending apps. Protecting customer data and keeping credit underwriting reliable matters. Device fingerprinting is a practical place to start.

• Integrating Fingerprint.com Device Fingerprinting with Decisimo

  This guide shows how to connect Fingerprint.com device fingerprinting with Decisimo. It walks through setup, API keys, and JavaScript implementation, then shows how to use the visitor_id in your decision logic to support fraud checks and device recognition.

• 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.