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Data Integrity & Fraud Prevention
DataAutomationllm-apps

Data Integrity & Fraud Prevention

16 вер 20264:00 PM - 5:30 PM GMT+00:00ОнлайнOpen

Опис

Explore modern survey fraud detection and data integrity in this 90-minute online Greenbook showcase on 16 September 2026, featuring live technology demos.As AI-generated responses grow more convincing, familiar quality checks such as identifying speeders, straight-liners and weak open-ended answers are no longer enough. Fraudulent respondents can use real devices, residential IP addresses and AI-generated verbatims to resemble legitimate research participants. This online Data Integrity & Fraud Prevention showcase examines how research teams can respond with stronger quality assurance before, during and after fieldwork.Presented by Greenbook | The Future of Insights, the session takes place on Wednesday 16 September 2026, from 4:00pm to 5:30pm UTC (12:00pm ET). The 90-minute format combines an introductory presentation from Greenbook, live demonstrations of fraud prevention technology and interactive Q&A.## What you’ll learnThe programme offers a practical overview of the changing fraud landscape and the technologies designed to protect research data. Topics include:- How generative AI has changed the economics and sophistication of survey fraud- Device and network forensics used to assess respondent authenticity- Behavioural biometrics and AI-based content scoring- Cross-panel identity and reputation systems- Incentive and payout verification tools- Video and voice authentication methods- The growing risks posed by professional respondents, duplicate identities, deepfakes, proxy networks and AI-assisted impersonation- Where different protection approaches overlap,and where their capabilities differBeyond reviewing individual categories of technology, the showcase will help attendees assess the market more critically. Expect guidance on recognising meaningful product differentiation, separating genuine innovation from marketing claims and asking vendors and suppliers more useful questions during technology evaluations.## Who should attend?…Register for this event

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# Data# Automation# llm-apps

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