Digital Payment Fraud Calculator
Fraud loss estimation from transaction volume and type.
About this calculator
This calculator models what card-not-present fraud actually costs a merchant, and whether a fraud-prevention tool is worth paying for. It starts from your monthly transaction volume divided by average transaction size to get a transaction count, then applies your fraud rate in basis points (10 bps = 0.1% of transactions) to find how many of those transactions are fraudulent. The gross fraud loss is just the face value of those transactions, but the calculator also applies a "true cost of fraud" multiplier — defaulting to 2.94, LexisNexis's industry-standard figure — because a fraudulent order actually costs a merchant the merchandise, shipping, the chargeback fee, and the labor to fight it, not just the transaction amount itself.
To evaluate a prevention tool, the calculator assumes it catches a set detection rate of fraud (blocking those transactions before they ship) while also blocking a small percentage of legitimate orders as false positives — a real cost, since those are lost sales, not saved ones. ROI is monthly savings (the gap between the true cost of unprotected fraud and the residual cost with the tool, including its subscription fee and false-positive losses) divided by the tool's monthly cost. The biggest lever most users overlook is the false-positive rate: a tool with a high detection rate but sloppy accuracy can silently cost more in blocked good customers than it saves in blocked fraud, so don't judge a fraud tool on detection rate alone.
Inputs
Results
True monthly fraud cost
$1,470.00
Monthly savings with tool
-$10,853.31
How to Use This Calculator
- Enter Monthly volume ($), Avg transaction ($), and Fraud rate (basis points).
- Set Chargeback fee ($), True fraud cost multiplier, and Fraud tool cost ($/mo).
- Adjust Tool detection rate (%), False positive rate (%) as needed.
- Review True monthly fraud cost ($) and Monthly savings with tool ($).
- Use Fraud tool ROI (%) (%) and Gross fraud loss ($) to inform your decision.
How the result changes with Monthly volume ($)
| Monthly volume ($) | True monthly fraud cost | Monthly savings with tool |
|---|---|---|
| 250,000 | $735.00 | -$6,426.65 |
| 375,000 | $1,102.50 | -$8,639.98 |
| 750,000 | $2,205.00 | -$15,279.96 |
| 1,250,000 | $3,675.00 | -$24,133.27 |
What each input means
- Monthly volume ($)
- Total dollar amount of transactions processed per month.
- Avg transaction ($)
- Average dollar amount per transaction.
- Fraud rate (basis points)
- Fraud rate in basis points. 10 bps = 0.1% of transactions. E-commerce average is 10-20 bps.
- Chargeback fee ($)
- Fee charged per chargeback by the payment processor (typically $15-25).
- True fraud cost multiplier
- Total cost per $1 of fraud (LexisNexis avg: $2.94). Includes lost goods, shipping, fees, and labor.
- Fraud tool cost ($/mo)
- Monthly cost of fraud detection/prevention tool (e.g., Sift, Riskified, Forter).
- Tool detection rate (%)
- Percentage of fraudulent transactions the tool successfully detects and blocks.
- False positive rate (%)
- Percentage of legitimate transactions incorrectly flagged as fraud (customer friction and lost revenue).
What each result means
- True monthly fraud cost
- Full cost of fraud including lost merchandise, fees, and operational costs (without prevention).
- Monthly savings with tool
- Net savings from using the fraud prevention tool (fraud reduction minus tool cost and false positives).
- Fraud tool ROI (%)
- Return on investment for the fraud prevention tool.
- Gross fraud loss
- Direct dollar value of fraudulent transactions per month.
- Fraudulent transactions
- Estimated number of fraudulent transactions per month.
- Chargeback fees
- Total chargeback fees from fraudulent transactions.
- Residual fraud (with tool)
- Fraud losses that remain after the prevention tool catches what it can.
- False positive revenue loss
- Revenue lost from legitimate orders incorrectly blocked by the fraud tool.
How this is calculated
Worked example, using the default values
- Identify Input Parameters4 parametersMonthly volume ($) = 500000, Avg transaction ($) = 65, Fraud rate (basis points) = 10, Chargeback fee ($) = 20 = 8 input(s) provided
- Calculate True monthly fraud costTrue monthly fraud cost = grossFraudLoss * fraudMultiplier1470 = $1,470
- Calculate Monthly savings with toolMonthly savings with tool = totalCostWithoutTool - totalCostWithTool-10853.31 = $-10,853.31
- Calculate Fraud tool ROIFraud tool ROI = fraudToolMonthlyCost > 0-542.67 = -542.67%
- Calculate Gross fraud lossGross fraud loss = fraudulentTransactions * avgTransactionSize500 = $500
Engine last updated . Checked against 2 independently-derived tests — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.
Frequently Asked Questions
Why does the calculator multiply gross fraud loss by 2.94 instead of just using the transaction amount?
A chargeback doesn't just cost the transaction's face value — the merchant also loses the merchandise (already shipped in most card-not-present fraud), pays return shipping or absorbs the loss entirely, owes the chargeback fee on top, and spends staff time disputing or writing off the case. LexisNexis's annual Cost of Fraud survey pegs this all-in multiplier at roughly $2.94 per $1 of fraud for typical e-commerce merchants, which is why the 'true cost' output runs nearly 3x the 'gross fraud loss' line even though both start from the same fraudulent-transaction count.
How can a fraud tool with a 70% detection rate still lose money?
The tool's savings come from the fraud it catches (true cost avoided) minus three things: the fraud it misses, its own subscription fee, and the revenue lost when it wrongly blocks legitimate orders. If your false-positive rate is set high relative to your fraud rate, the false-positive revenue loss can exceed what the tool saves in blocked fraud, since legitimate orders usually far outnumber fraudulent ones even at a 'bad' fraud rate. That's exactly the scenario worth checking with the ROI output before signing a contract.
What does the fraud rate in basis points actually mean for my store?
One basis point equals 0.01% of transactions, so a fraud rate of 10 bps means 1 in 1,000 transactions is fraudulent, and the calculator's default assumes e-commerce's typical 10-20 bps range. It multiplies this rate directly against your monthly transaction count (volume divided by average ticket size) to estimate how many fraudulent orders you're processing before any prevention tool intervenes.
Should I count chargeback fees separately from the true fraud cost, or are they already included?
They're tracked separately in this model. The true fraud cost multiplier (2.94x) already accounts for typical operational and fee overhead in the aggregate, but the calculator still adds the chargeback fee per dispute as its own line item in the total cost, since that's a fixed, known dollar amount charged by your processor per fraudulent transaction regardless of the merchandise value involved.
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