Data Quality, Fraud Prevention & Compliance
Mapping Survey Fraud & Security Features
Survey fraud is increasingly complex. Veridata Insights addresses this with a four-step strategy: integrating software from three industry-leading fraud detection firms into SampleTap to block or monitor suspicious participants; using programmatic checks within surveys; applying human review by experienced project managers; and factoring in client feedback to track emerging trends. Survey fraud remains an ongoing challenge, and this document outlines the features and processes we use to maintain survey integrity.
The Fence – a Triple Layered Line of Defense to Detect & Prevent Fraud
The Fence combines the strengths of three industry leading firms arming us with superior automated survey fraud detection.
| Feature | Purpose / Function |
| Advanced Fingerprinting (40+ Forensic Markers) | Detects bots, emulators, simulators, proxies, and duplicate entries. |
| ChatGPT Blocking | Prevents AI-driven bots from completing surveys. |
| Auto-Translation Detection | Flags auto-translated responses indicating fraud or low-quality participation. |
| Attention & Honesty Verification | Identifies inattentive or dishonest respondents. |
| Sample Quality Tracking Monitor | Real-time monitoring of sample quality to detect suspicious patterns. |
| Multi-Level Protection & Flexible Integration | Tailors fraud prevention measures to specific survey projects. |
| Adaptive Recognition | Updates algorithms to counter evolving survey fraud tactics. |
| Device Oscillation & Velocity Analysis | Flags hyperactive respondents attempting multiple surveys rapidly. |
| JavaScript Integration | Enables real-time detection on survey landing pages. |
| Active Forensics Across Multiple Signals | Detects sophisticated fraudsters, fake accounts, and bots in real-time. |
| Modern Proxy & VPN Detection | Identifies respondents masking location or identity. |
| Email Deep Research | Detects disposable or fraudulent email accounts. |
| Behavioral Bot Detection | Differentiates between genuine respondents and bots. |
| True Location Verification | Prevents location spoofing and ensures sample integrity. |
| Passive Geographic Verification | Uses location-specific questions to confirm respondent authenticity. |
Programmatic Checks and Security
Leveraging powerful tech is one step, however, in order to stay ahead of the most aggressive fraudsters, it is important to think about security within the survey itself.
- Invisible Security Passkey: Creates an invisible “handshake” between SampleTap and our programming platform so that we can instantly recognize if someone has tampered with their entry links to the survey.
- Hidden Questions: These are a unique, open ended, question that we place within the survey. It is invisible to the human eye, but a bot will “see” and answer it just like any other question.
- Copy Paste Detection and Prevention: Encourages survey responses which are more likely to be in the words of the survey participant.
- AI-Probing: The ability to leverage AI to review an open ended response in real-time and ask additional questions in order to encourage a more robust response.
Human Review
- Review of leading questions: When reviewing the survey screener, recommending changes to ensure that the questions do not unintentionally lead a respondent to the response that will allow them to continue in the survey.
- Open End Review: A manual review of open-ended survey responses checking for batched responses or similar indicators of fraudulent activity.
- Red Herrings: Inserting an unusual or obviously incorrect option within a question or adding a fabricated question that attentive respondents should easily recognize as invalid.
- Logical Inconsistencies: Mechanism that identifies contradictions or illogical patterns in a respondent’s answers. It ensures that responses across related questions are logically consistent.
- Screen Recording: Before respondents enter a survey, we ask them a few questions, including one open ended response. If certain participants seem to be answering programmatically, we can visually review their screen when they were answering the questions.
- Length of Interview Management: Determining the correct thresholds from soft launch data to identify unusually short durations or unusually long durations for survey completion. This helps to weed out those who are inattentive, confused or fatigued.
Client Feedback Loop
While internal checks help identify poor-quality respondents, our clients are experts in their fields of study. They can identify suspicious patterns, unrealistic responses, or demographic inconsistencies that may not be obvious to our team or easy to catch programmatically. When clients flag quality issues, it creates a feedback loop that holds sample sources, like Veridata Insights, accountable. Tracking these issues over time allows us to monitor performance, enforce standards, and remove underperforming sources. This iterative approach fosters a culture of continuous improvement and helps maintain compliance with industry ideals.
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