See how top providers are tackling survey fraud, AI threats, and data quality challenges with live demos and expert insights.
As AI-generated responses become more sophisticated and fraudulent respondents increasingly mimic legitimate participants, protecting data quality has become one of the biggest challenges facing the insights industry. Traditional signals like speeders, straight-liners, or weak open-ends are no longer enough. Fraudsters now use real devices, residential IPs, AI-generated verbatims, and increasingly complex tactics that make poor-quality data harder to identify and remove.
Data Integrity & Fraud Prevention is an upcoming Greenbook Insights Tech Showcase dedicated to helping research, operations, and insights professionals understand the rapidly evolving landscape of fraud detection and quality assurance technologies.
Taking place on Wednesday, September 16 at 12:00 PM ET, the event combines an introductory presentation from Greenbook with live technology demonstrations and interactive Q&A sessions.
Why This Topic Matters
Generative AI has fundamentally changed the economics of survey fraud. Respondents can now produce coherent, contextually relevant answers in seconds, making many traditional quality checks ineffective. Meanwhile, professional respondents, duplicate identities, deepfakes, proxy networks, and AI-assisted impersonation continue to increase the complexity of ensuring trustworthy data. Modern data quality challenges extend far beyond simple survey cleaning and require prevention mechanisms that operate before, during, and after fieldwork.
What You'll Learn
Participants will gain a comprehensive understanding of:
- The current fraud landscape and how AI has changed respondent quality challenges.
- Different categories of protection technologies, including:
- Device and network forensics
- Behavioral biometrics
- AI-based content scoring
- Cross-panel identity and reputation systems
- Incentive and payout verification tools
- Video and voice authentication methods
- Where various solutions overlap and where they differ.
- How to distinguish genuine innovation from marketing claims.
- Which capabilities represent meaningful differentiators in modern fraud prevention platforms.
- Questions to ask vendors when evaluating technologies and suppliers.
