Comparative Results from Five Leading Fraud Detection Platforms

Automation has reshaped online research—and introduced new risk. Fraudsters now mimic real human behavior, while detection platforms often disagree on what constitutes fraud.

This report exposes where performance gaps occur, how they impact data quality, and why relying on a single tool can quietly compromise insights.

Inside your exclusive report:

• Independent Platform Benchmarking — Side-by-side evaluation of five fraud detection tools tested on identical respondent samples

• Where Tools Disagree — Pass/fail agreeability analysis revealing hidden inconsistencies in fraud logic

• Audience-Specific Risk — Why Consumer, B2B, and Healthcare studies produce very different fraud outcomes

• Failure Pattern Insights — The most common triggers behind false positives and missed fraud

• What Actually Works — Why layered detection, human review, and transparency deliver stronger data