The Three Shields: A Proactive Blueprint to End Survey Fraud

 As a recent Kantar report highlighted, researchers are discarding up to 38% of collected data due to quality concerns and fraud. The reactive game of whack-a-mole with bots isn’t working — and it’s draining budgets and trust.

The way forward isn’t better detection. It’s better prevention. Fraud needs to be stopped before it ever enters your dataset. That requires a proactive framework built on three shields:

1. The Bot Check: Stop Non-Humans at the Door

Most fraud is automated. By screening a respondent’s digital footprint at registration for non-human patterns, you stop bots before they ever touch a survey.

This isn’t about cleaning data later — it’s about never letting fraud in to begin with.

2. The Match Check: Verify Identity

Fraud isn’t always robotic. Human scammers will sometimes pretend to be people they are not, these people could be real or completely fabricated. The second shield confirms that the name, email, and location provided during a survey match the verified identity of the panelist.

This simple step dismantles the business model of professional survey takers who operate multiple aliases, ensuring integrity from the start.  

3. The Cross Check: Double checking survey responses

Why ask people to self-report what you can already confirm? Pulling in verified professional and demographic signals directly from existing digital records reduces survey fatigue and speeds up the data collection process.

The other benefit of this is it allows you to check against overclaims and exaggeration, and ensures you’re working with truth.

From Defense to Offense

Chasing fraudsters is an endless, costly war. Prevention changes the game. With these three shields, you don’t just clean up bad data — you remove the incentive for fraud altogether.

That means fewer wasted responses, more reliable panels and insights you know are real.