Fraudulent completes, direct cost
Every fraudulent respondent who passes QC is paid for at the agreed CPI. The most direct, most quantifiable fraud cost.
Six fraud-cost levers, priced against your own numbers. See what fraud costs your agency today, before, during, and after fieldwork, and what SurveyGuard recovers.
Fraud cost dimensions
6 levers
False positive rate
< 1%
Per-respondent verdict
< 200ms
Unlike the FieldworkOS calculator (operational time and CPI), this focuses entirely on the data-quality cost dimension. Tune the inputs and the six levers recompute live.
Section A
Spend, CPI, fraud rate, and what your current QC catches. These drive every fraud-cost lever.
Median cluster $250K–$500K for mid-size agency PMs.
62% of PMs reported $3–5. Default $4.50.
~22% with basic speed + attention checks; ~45% unprotected.
75% of PMs use basic QC only, catching ~40–50%.
Section B
Headcount and how fast studies turn over, which sets cleaning labour and re-field volume.
Everyone who spends time on fieldwork QC and reconciliation.
Drives the post-field cleaning labour cost (F4).
Combined with field duration to derive annual study volume.
Shorter fields → more studies/year → more exposure.
Section C
How often fraud forces a re-field, and how often a mid-study CPI change quietly inflates billing.
75% of PMs reported re-fields. ‘2–3/year’ most common ≈ 12%.
38% of PMs quantified at $5K–$10K. Default $7,500.
Archit reported 10–25%. Conservative default 20%.
Section D
The most variable lever: client-facing quality events that reach delivered data.
Set to 0 if you’ve had no recent client quality events.
Sample + PM + reporting + margin for a mid-size study.
SurveyGuard · fraud cost
Six fraud-cost levers. Set your inputs on the left, then run the numbers. Results stay hidden until you calculate.
Your full ROI breakdown appears here once you calculate.
Every fraudulent respondent who passes QC is paid for at the agreed CPI. The most direct, most quantifiable fraud cost.
When fraud contaminates a dataset beyond repair, the study is re-run. 75% of PMs reported re-fields; 62% quantified them at $5K–$10K each.
Fraudulent respondents fill quota cells and turn genuine respondents away. The hidden cost post-field cleaning can never recover, so prevention is the only route.
75% of PMs spend hours per study reviewing open-ends, removing speeders, and matching IDs. Salaried time SurveyGuard eliminates at entry.
Mid-study CPI changes plus fraud-inflated completion counts mean agencies overpay. 75% reconcile in manual Excel, a low catch rate.
When fraud reaches delivered data and a client raises a concern: re-work, credits, and renewal risk. The most variable lever, but the insurance value is real.
Every default is backed by real answers from the 100+ project managers, across small agencies to enterprise firms, who completed the SoftSight questionnaire. When a prospect challenges a number, every assumption has a source.
| Calibration input | Value |
|---|---|
Fraud rate with basic QC 87% of PMs identified fraud types · industry ~22% with speed + attention checks | 22% |
Current QC catch rate 75% use basic QC only · speed + attention catches ~40–50% of fraud | 45% |
Average CPI 62% of PMs reported $3–5 · validated default | $4.50 |
Re-fields driven by quality/fraud All quantified re-fields were quality-driven | 60% |
Re-field cost per event 38% of PMs quantified at $5K–$10K · midpoint | $7,500 |
SurveyGuard re-field prevention Real-time detection prevents quota contamination before re-field | 75% |
Quota contamination rate Conservative, since hard-to-reach cells contaminate more | 35% |
Cleaning hours per study 75% of PMs spend 2–5 hrs post-field cleaning | 3.5 hrs |
Cleaning reduction with SurveyGuard Fraud caught at entry needs no cleaning; 30% non-fraud remains | 70% |
Mid-study CPI drift rate Archit 10–25% · conservative default | 20% |
Manual reconciliation catch rate 75% manual Excel · ~12% trusted supplier blindly | 15% |
Twenty minutes in your browser. The walkthrough is run by someone who has lived the workflow you’re trying to leave behind, not a salesperson reading from a deck.