5 research fraud signals your incentive platform should monitor
By Abby Quillen●6 min. read●Jan 8, 2026
Your research depends on data integrity, and dishonest survey participants can undermine it at every step. They may misrepresent eligibility, participate multiple times under different identities, or use AI to generate fake responses.
These behaviors are contributing to a significant decline in data quality. According to one recent study, usable responses from online research have fallen from 75% to 10% in recent years due to research fraud. And in a recent Tremendous survey, 46% of respondents cited fraud as a moderate to major challenge for their research programs.
If you’re like most research teams, you already rely on multiple recruitment and in-survey fraud controls to weed out scammers. Even so, fraudsters can slip through, degrade your data quality, and drain your incentive budget.
Your incentive platform can serve as a final checkpoint in the fraud prevention process. By cross-checking signals from your recruiting and survey tools and adding incentive-specific indicators, a sophisticated incentive platform helps identify and block bad actors before reward payouts. In this guide, you’ll learn why incentive fraud detection is a critical safeguard and which five key signals your incentive provider should monitor.
Key takeaways
While upstream fraud prevention tools check for fraud in responses, emails, and basic metadata, they don’t have access to redemption- and payout-specific data. Incentive platforms can use this data to uncover incentive fraud patterns that don’t appear in earlier checkpoints.
Incentive platforms should check for the following five fraud signals:
Reused IP addresses at redemption
Country mismatches during incentive redemption
Multiple emails tied to the same device
Duplicate bank or payout details
Network-wide redemption patterns
Why your research incentive platform is the last line of defense against fraud
There’s no single tool that can detect every fraud signal, so most teams rely on several layers of fraud prevention. At the participant payout stage, your incentive platform provides the final critical layer of protection for identifying and blocking fraudulent participants before they deplete your research budget.
Survey-level detection methods
What they look for: These tools offer comprehensive monitoring inside your survey. They analyze IP addresses, device types, and browsers to look for bot patterns, device anomalies, and behavioral red flags. They’re the foundation of most prevention strategies, and they can help you detect low-quality or ineligible responses.
Fraud prevention gaps: They often miss bots that use sophisticated AI to mimic normal completion times, pass attention checks, and generate plausible answers.
Verification and authentication tools
What they look for: These tools analyze open-ended responses to flag AI-generated text by looking for indications like perfect grammar and formulaic phrasing.
Fraud prevention gaps: As AI responses become more natural-sounding, they’re more likely to slip through these checks.
Data cleaning tools
What they look for: These tools analyze data after a study to detect off-topic responses, gibberish, and repeated answers. They reduce the risk of bad data affecting your survey results.
Fraud prevention gaps: They weed out junk data, but only after participants are paid, so they won’t stop you from wasting budget on bad actors.
In-house screening tools
What they look for: Teams build these internal tools to screen for patterns specific to their methodology.
Fraud prevention gaps: They require ongoing development and maintenance, and often rely on a human-powered review process that can miss more subtle fraud signals.
Incentive fraud detection
These tools provide a final safeguard in case fraudsters have slipped past other layers of protection. They examine IP addresses, countries, and email addresses at the incentive payment stage to look for suspicious redemption behavior. They help you catch bad actors before you send payouts to save your research team money.
5 fraud signals to monitor from your incentive platform
Top incentive solutions provide fraud controls that ensure legitimate participants receive payments and bad actors are excluded. Your platform should have built-in fraud monitoring features to identify the following five indicators:
1. Reused IP addresses across multiple participants
Your platform should check for multiple respondents trying to redeem rewards from a single IP address, device, or network within a short window. While multiple people in a household or workplace may legitimately take the same survey, a large number of participants redeeming incentives in a short period from the same location often indicates fraud. For example, if 40 people redeem rewards from the same IP within 20 minutes, your team should probably take a look before incentives are paid out.
2. Participant country mismatches
Make sure your platform uses geolocation data to cross-check a device’s time zone, stated geolocation, and language settings to identify inconsistencies. Fraudulent participants sometimes appear to complete a survey from one country while redeeming rewards from another. For example, a participant’s profile may say they’re from the U.S, but they redeem rewards from a different country a few minutes after completing the survey.
Geolocation irregularities can also indicate a participant is using a virtual private network (VPN) or proxy, location spoofing app, or browser extension to make it look like they meet a survey’s eligibility requirements. In one analysis, geolocation outside the study area was the most frequent violation of study criteria, with nearly 40% of responses flagged for potential fraud for that reason. The incentive stage offers a critical opportunity to double-check for location discrepancies and identify bad actors that may have gotten past earlier checks.
3. Multiple emails tied to the same device
Your platform should identify participants who take studies multiple times by creating large numbers of disposable email addresses or by rotating through fabricated identities linked to different email addresses. For example, if 12 unique respondents with distinct email addresses redeemed rewards from the same device in one week, it likely signifies fraud.
Upstream recruiting or in-survey detection tools can miss multiple emails tied to a single device because they only check that email addresses are unique. Digital fingerprinting at redemption identifies various characteristics of devices — such as the operating system, browser version, screen resolution, and more — to tie email accounts to devices.
4. Reused bank account or payout information
It’s pretty easy to spin up multiple emails or spoof IPs, but it’s a lot harder to fake financial information. When multiple participants use the same payment information — whether it’s a bank account, PayPal, Venmo, or other financial account — it’s a clear sign that something is fishy. For example, if 30 survey respondents routed payments to the same bank account, your platform should flag it as suspicious and allow you to block questionable transactions.
Reused bank or digital payment account information is one of the clearest indicators of incentive fraud at the redemption phase. Recruiting and in-survey tools don’t capture financial data, so they miss these bad actors, making detection at the incentives phase essential.
5. Network-wide redemption pattern intelligence
Your research team only has data on recipients who’ve participated in previous studies. An incentive platform, however, has access to a much broader network of recipient data — and if it includes fraud prevention tools, a history of blocked participants. Tapping into this existing network can help you block known fraudsters faster. This final check catches individual bad actors, groups of people, or bots who’ve already been flagged by other organizations and might slip under the radar otherwise.
Summary
Upstream tools identify and catch fraudsters at the recruitment and survey stages, but fraud can still slip through. Incentive fraud detection offers a critical final layer of protection to flag and block scammers before money goes out the door.
Your incentive platform should detect the five fraud signals discussed above before payouts. It should also let you customize your detection rules for your audience and survey design. For example, in a B2B survey, many participants may work in the same office, so your rules should allow multiple participants from the same IP address. In a global consumer survey, on the other hand, you may need stricter geolocation matching to verify eligibility. With the right protections in place at the incentive stage, you’ll protect your data integrity and your budget.
