Why the fraud tool roi calculator matters
Fraud tools are sold on catch rate and paid for in false declines — the good customers turned away rarely appear in the vendor's ROI model. This page turns that decision into a handful of inputs you can defend in a budget review: volume, unit cost, rate of adoption, and time. The output is a planning baseline, not a promise — it tells you whether the idea deserves a vendor quote, a pilot, or a pass.
- • Biggest swing factor: average loss per fraudulent order
- • Second-order factor: catch rate
- • Often ignored: false decline rate, which is a hidden revenue cost
What actually changes the answer
average loss per fraudulent order moves this number first, then catch rate. Run a conservative case and an upside case before you commit. If the maths only works in the upside case, treat it as a time-boxed test with a kill date rather than a line in next year's plan.
What to do with the result
Ask the vendor for false-decline rate in writing and multiply it by your order volume and AOV. Subtract that from the savings here before signing.
FAQ
What does the fraud tool roi calculator work out?
It applies Net savings = (volume × reduction rate × cost per event) − tool cost to the values you enter for fraudulent order attempts per month, attempts the tool blocks, average loss per fraudulent order, fraud platform per month. Fraud tools are sold on catch rate and paid for in false declines — the good customers turned away rarely appear in the vendor's ROI model.
How accurate is this fraud tool roi calculator?
Models blocked losses only. A one-point false decline rate on a high-volume store can exceed the fraud saving entirely. Replace the defaults with your own invoice, usage export, payroll data, statement, or vendor quote before making a commitment — the maths is exact, so the answer is only as good as the inputs you feed it.
Which input should I stress-test first?
average loss per fraudulent order. Re-run with a pessimistic value for it; if the decision flips, that assumption is the thing you need real data on before signing anything. After that, check catch rate and false decline rate, which is a hidden revenue cost.
Which scenario should I start from?
Start with the preset closest to your situation — lean case, expected case, scaled case — then edit the sliders. Presets are realistic starting points, not benchmarks to match, and every change updates the result instantly.
What should I do after running the numbers?
Ask the vendor for false-decline rate in writing and multiply it by your order volume and AOV. Subtract that from the savings here before signing. A useful planning benchmark to compare against: Screening tools catch 70–90% of attempts, with 0.5–3% false declines.
Can I share or save this calculation?
Yes. Your inputs are written into the page URL, so copying the link shares the exact scenario you are looking at — the person who opens it sees the same numbers. You can also export the inputs and results to CSV or PDF from the result card and keep it with the rest of your workings.
How this calculator is built
Independently maintained
Written by Sam Doshi and the RevenueLab editorial team. We don't sell the data feeds this tool is built on.
Sourced from primary data
Benchmarks come from public AdSense / Stripe / IRS disclosures and reader-submitted data — never third-party "$X per view" claims. Full methodology.
Last editorial review
Reviewed on a rolling quarterly cycle. Dated reviews are published on the methodology record for each calculator.
Editorial standards
See our editorial policy and disclaimer. Results are estimates, not advice.