Research fraud prevention: How to build your tech stack
Tremendous and Escalent interviewed research leaders about the impact of AI-powered participant fraud. Explore their proven detection methods and the latest tools for protecting your studies at every stage.
Your complete guide to research fraud detection tools
With 30-40% of research data now impacted by fraud, knowing which detection tools to deploy has become critical for protecting data integrity. This practical guide provides a fraud prevention framework that leading research teams are using to combat participants using generative AI tools and AI agents to game the system.
Explore the detection methods, top tools, and strategies leading research teams are using to inform your team’s fraud prevention tech stack.
What you'll learn
Why AI responses slip past traditional fraud checks, and the behavioral, linguistic, and payout signals that expose them
How a 5-stage fraud prevention playbook and vetted tools can help your team remove bad actors throughout the research process
How to layer tools into a cost-effective tech stack that safeguards data integrity without adding friction for real participants
“We're paying out millions in incentives to fraudsters. Without proper detection tools, researchers may unknowingly reward bad data and waste valuable time and resources.”
— John LaFrance, Vice President of Research Methods and Sampling Operations of Escalent