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Case StudiesSurvey fraud has escalated dramatically with sophisticated bots, VPN-masked participants, and AI-generated responses threatening data integrity. Zamplia's Calibr8 fraud detection system, launched in June 2025, leverages machine learning algorithms analyzing behavioral and technical signals to identify fraudulent responses in real-time during survey completion. In validation testing across 43 distinct respondent sources, Calibr8 flagged 32% of completes as potentially fraudulent or poor-quality-demonstrating both the scale of the threat and the value of comprehensive fraud detection.​
Survey fraud has escalated dramatically with sophisticated bots, VPN-masked participants, and AI-generated responses threatening data integrity. Zamplia's Calibr8 fraud detection system, launched in June 2025, leverages machine learning algorithms analyzing behavioral and technical signals to identify fraudulent responses in real-time during survey completion. In validation testing across 43 distinct respondent sources, Calibr8 flagged 32% of completes as potentially fraudulent or poor-quality-demonstrating both the scale of the threat and the value of comprehensive fraud detection.​
Beyond bots, Calibr8 addresses sophisticated human bad actors-professional survey takers who fabricate qualification criteria to access lucrative studies, participants who rush through surveys collecting incentives without genuine engagement, and duplicate respondents attempting multiple completions. Our system cross-references digital fingerprints through device fingerprinting, IP tracking, and browser configurations to identify duplicates even when respondents attempt to mask their identity through VPNs and browser privacy tools.
The most challenging fraud threat involves AI-generated survey responses. Large language models can produce human-like open-ended responses that pass basic coherence checks. Calibr8's AI detection mechanisms analyze linguistic patterns, response consistency with profile data, and semantic coherence across multiple open-ended questions to flag AI-generated content. Our eight-layered approach combining AI detection with behavioral biometrics, metadata validation, and coherency scoring provides comprehensive protection against evolving fraud techniques.​​