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Benchmarks (Operator Field Manual)

TL;DR
  • Auth rate: Visa's 2025 analysis reports overall U.S. approval rates below 87%, using VisaNet data from April 2023 to March 2025. No public source breaks that down by channel or for small merchants. Compare card-not-present (online and phone) and card-present (in-person) baselines; ask your processor for peers
  • Dispute programs: U.S. Visa VAMP excessive starts at 1.5% with 1,500 combined fraud reports and disputes, when your acquirer (the bank behind your processor) isn't Above Standard or Excessive; Mastercard ECM at 100 to 299 chargebacks this month AND 1.50 to 2.99% of last month's Mastercard sales; HECM is 300+ AND 3.00%+. Your processor can set a stricter limit. Get it in writing
  • Fraud: MRC's global merchant survey: 3.5% of accepted orders later found fraudulent. Fed research: in-person fraud value on non-prepaid U.S. debit cards at big covered issuers, on dual-message networks, ran 0.142% in 2023. They measure different things
  • Refunds: No published all-merchant norm. Read refunds and disputes together
  • Segment everything: CP vs. CNP, BIN (the card number's opening digits), geo; trend over 4-8 weeks beats snapshots

Key Fact: Your processor can act before a network threshold. Ask: "What's my limit, how's it calculated, and when will you contact me?" See Network Programs for regional conditions, acquirer tiers and fees.

You're here to grade your numbers. Use anchors, not absolutes. Compare to yourself over time and by segment (card-present vs card-not-present, method, BIN, geo). Your baseline matters more than industry averages.

1.5%
NETWORK Visa VAMP excessive, U.S., with 1,500 fraud reports and disputes a month, when your acquirer isn't Above Standard or Excessive
100-299 and 1.50-2.99%
REPORTED Mastercard ECM starts: chargebacks this month, ratio against last month's Mastercard sales
0.142%
REPORTED In-person fraud value, non-prepaid U.S. debit at big covered issuers on dual-message networks, 2023 (Fed data)
Not published
U.S. approval rates by channel or merchant size: no public source

Sources checked: 21 October 2026. Where no figure is shown, use your own cohort baseline; the published figures below apply only to their stated populations.

How to read these numbers​

  • Segment everything. CP vs CNP, card brand, BIN/issuer, country, device. Aggregate numbers hide problems.
  • Trend beats snapshot. Direction over 4-8 weeks matters more than any single week.
  • Read metrics together. Auth, fraud, chargebacks, refunds, and alerts are interconnected.
  • Match the source's population. A global merchant survey isn't a US domestic target. Check channel, geography and MCC (your business category code) before comparing.
  • Date your thresholds. "Last verified" on any number you publish or operationalize.

Authorization Rate Benchmarks​

NETWORK Visa reports overall U.S. approvals below 87% in its 2025 analysis, using VisaNet data from April 2023 to March 2025. Visa doesn't give a channel split or merchant-size breakdown for that figure, so don't grade either channel against it. It isn't your target.

Card-Not-Present (CNP)​

NOT PUBLISHED Universal CNP performance bands.

  • Pull decline codes by issuer, device and country
  • Check fraud rules, 3DS failures (the extra checkout verification) and abandonment
  • Test tokens and retries; watch fraud and disputes too

Card-Present (CP)​

NOT PUBLISHED Universal retail approval bands.

  • Check terminals and connectivity when approvals drop
  • Separate chip, contactless and keyed entry

By Payment Method​

MethodPublished comparison pointWhat to check
Cards (CNP)Not publishedBIN and issuer segments
Cards (CP)Not publishedEntry mode and terminal
Apple Pay/Google PayNot publishedEach wallet against matched card-entry traffic
PayPalVENDOR 95% suggested target, authorize-now, capture-later integration, updated 8 July 2026This isn't an observed average or ranking
ACHNot publishedSettlement and returns, separately from card approvals

By Issuer Geography​

NOT PUBLISHED Regional ranges or cross-border gap.

  • Compare countries and issuers within the same channel
  • Separate authentication failures from issuer declines
  • Ask: "How do I compare with similar merchants here?"

Fraud Rate Benchmarks​

By Transaction Type​

TypePublished contextWhat to check
Global e-commerce, across payment methodsREPORTED 3.5% of accepted orders later found fraudulent. Merchant survey, MRC 2026 report, Figure 27, p.36Accepted orders, not dollars lost
CP, U.S. non-prepaid debitREPORTED 14.2 bps (0.142%) on networks like Visa and Mastercard; 5.1 bps (0.051%) on PIN networks like Star, NYCE and Pulse, by value in 2023. Kansas City Fed research briefing, 25 February 2026, Chart 3Large banks only; losses to all parties, not just merchants
Digital goodsNot publishedProduct and delivery method
SubscriptionsNot publishedInitial versus recurring payments

MRC surveyed global merchants in November and December 2025. Its trimmed average covers the preceding 12 months. It isn't a U.S. card target. Fed coverage: debit cards from banks with $10 billion or more in assets. Neither sets your target.

By Industry (CNP)​

NOT PUBLISHED Industry ranges or ranking.

  • Retail and high-ticket: separate products; read dollars beside order counts
  • Digital goods: check access and delivery evidence
  • Travel: separate booking date from service date
  • Gaming and crypto: separate payment fraud from account abuse, trading and transfer losses

Fraud Detection Metrics​

MetricPublished contextWhat to check
False positive rateNot publishedConfirmed legitimate fraud blocks / All fraud blocks; keep unknowns visible. Use Fraud Metrics
Catch rateNot publishedConfirmed fraud missed, by rule and segment
Manual review rateREPORTED 21% of orders screened manually, average. MRC merchant survey, Figure 31, p.40Queue size, staffing and outcomes
Review-to-block rateREPORTED 18% of manually screened orders subsequently declined, average. MRC merchant survey, Figure 31, p.40A decline isn't proof of fraud

Figure 31 has 564 respondents in the same wave. These aren't cutoffs. Check fraud type, existing tools and good customers blocked before tightening rules.


Chargeback Benchmarks​

Chargeback Ratio Thresholds​

NOT PUBLISHED Universal healthy, danger or crisis bands.

  • Watch your trend against your processor's written limit
  • Start remediation when you're approaching it
  • Got a warning? Confirm its metric and deadline; use the emergency playbook

Network Program Thresholds​

Visa counts monthly card-not-present VisaNet fraud reports plus disputes over settled transactions, subject to exclusions. Its merchant test applies when the acquirer isn't Above Standard or Excessive. Mastercard uses this month's chargebacks over last month's transactions.

NetworkPublished monthly threshold
Visa VAMP, U.S.NETWORK At least 1.5% and 1,500 combined fraud reports and disputes, since 1 April 2026. Visa public fact sheet
Mastercard ECMREPORTED Acquirer documentation: 100-299 chargebacks AND 1.50-2.99%; HECM: 300+ AND 3.00%+. Braintree ECP guide, thresholds effective October 2019
American ExpressNETWORK US fee after three straight months over 1% (a location's chargebacks minus reversals, against its sales minus refunds). Fraud Full Recourse counts fraud by value against your Amex sales in every region: 0.9% AND USD 25,000 in a month brings a program notice, and three straight months under either line after it avoid the lower-tier penalties; at 1.8% AND USD 50,000 penalties start at the notice. Conditions and ECI detail: Amex's published chargeback and fraud lines. Source: Amex Merchant Rules, October 2026, sections 9.9, 9.11.4 and 12.4.4
DiscoverGet Discover's current numeric limit and its measurement terms from your acquirer in writing

Program owner: Network Programs.

Amex runs a closed loop and prints its lines in its Merchant Rules (October 2026): a US chargeback fee line and all-region fraud lines, with a judgment call left for chargebacks or inquiries that look "disproportionate". For Discover, get your current monitoring limit from your acquirer in writing. Its 2011 regulations mention excessive returns or disputes as a security trigger, without setting a number; that's an old trigger, not proof of today's sole standard.

Chargeback Composition​

NOT PUBLISHED Reason-share targets or diagnostic cutoffs.

  • Fraud-coded disputes: review purchase and delivery evidence before assuming stolen-card fraud
  • Unrecognized charges: check the billing descriptor (the name on your customer's statement) and purchase reminders
  • Service and recurring billing: check complaints, renewal notices and cancellation requests

Note: A fraud reason code alone doesn't tell you who made the purchase. Friendly fraud can appear in fraud-coded disputes. Use your order evidence to classify cases; don't use an industry estimate as your expected share.


Refund Benchmarks​

Refund Rate​

NOT PUBLISHED All-merchant refund bands.

  • Check access to eligible refunds; read disputes alongside refunds
  • Investigate changes by product, delivery, season and support issue

Refund-to-Chargeback Ratio​

NOT PUBLISHED Healthy ratio.

  • Use the same period; keep both counts beside the ratio
  • Check refund delays, duplicate credits and policy abuse
  • Are earlier refunds resolving problems and reducing disputes? Measure it

Alert Performance Benchmarks​

Ethoca/CDRN/Verifi Metrics​

NOT PUBLISHED Universal match, refund or prevention targets.

  • Track covered disputes against your issuer and card mix
  • Check prior refunds and duplicates before issuing credit
  • Measure prevented disputes before and after deployment

Real-Time Alert Response​

ProductPublished response guidance
Ethoca through KountVENDOR Respond within 24 hours; prevention or credit eligibility isn't guaranteed after that. Kount guidance, updated 5 August 2026
Verifi CDRNVENDOR Participating sellers refund within 72 hours. Verifi RESOLVE
Verifi RDRVENDOR Automatic decisions in real time, using seller rules

Use your provider's agreed deadline. A reporting window isn't a reason to wait.


By Business Model​

Subscriptions​

MetricPublished context
Initial auth rateNot published
Recurring auth rateNot published
Involuntary churnNot published
Dunning recoveryVENDOR 12.7% median attempted recovery among 119 active U.S. B2B SaaS customers using Baremetrics Recover, May 2026. Baremetrics measurement
Subscription fraudNot published

Baremetrics excludes failures it didn't attempt and accounts with no attempts. It isn't recovery over all failures. Separate initial payments, renewals and retries; track payment-driven churn by billing cycle.

Digital Goods​

NOT PUBLISHED Auth or fraud bands.

  • Split approvals by issuer, country and authentication flow
  • Dispute win rate: track it separately. Access and delivery records are your proof

Physical Goods​

NOT PUBLISHED Auth, fraud or not-received-share bands.

  • Investigate not-received claims by carrier and fulfillment route
  • Dispute win rate: track it separately by reason code and carrier. For not-received claims, check your delivery records

Track your own win rate by reason code.

B2B​

MetricPublished context
Auth rateNot published
Fraud rateNot published
ACH return rateNot published
Invoice payment termsREPORTED 46 days average agreed terms from invoicing. Atradius merchant survey: 240 U.S. companies, fielded late Q2 to mid Q3 2025. 2025 report, printed pp. 10 and 13

Agreed terms aren't time taken to pay. Separate ACH return reasons from card disputes.


Keyed Transaction Benchmarks (CP)​

NOT PUBLISHED Normal keyed-entry share.

  • Investigate a rise by terminal and employee
  • Check terminal issues, training gaps and CNP transactions recorded as CP
  • Review unexplained keying for employee fraud; log why entry was needed

Benchmarks by Revenue Tier ($50K-$5M)​

MRC defines SMB as $50K to under $5M annual e-commerce revenue (Figure 2, p.4). It doesn't publish subtier targets. Revenue isn't a performance ranking.

MetricPublished context for the whole SMB band
Auth rate (CNP)Not published
Fraud rateREPORTED MRC merchant survey: 3.4% of annual e-commerce revenue lost to payment fraud; 3.3% of accepted orders later found fraudulent over the preceding 12 months. Trimmed averages, Figure 27, p.36
Chargeback ratioNot published
Refund rateNot published
Processing costNot published
Manual review rateREPORTED MRC merchant survey: 21% of orders screened manually, average; SMB base 127, Figure 31, p.40
Reconciliation methodNot published

These share the survey period above. Match reconciliation tools to count and complexity. Costs need inputs:

Where the processing-cost range comes from

The fixed per-transaction cents punish small tickets. VENDOR Square's U.S. Free plan charges 2.6% + 15c for tap, dip or swipe in person, and 3.3% + 30c on Square Online and invoices. Its Online API rate is 2.9% + 30c, and manual entry is priced separately; the table below uses the tap, dip or swipe and Square Online figures. These effective rates are DERIVED: percentage rate + (fixed fee / ticket x 100).

Average ticketIn person (tap, dip or swipe), 2.6% + 15cSquare Online and invoices, 3.3% + 30c
$253.20%4.50%
$502.90%3.90%
$1002.75%3.60%

A small online seller with a $50 average ticket is at 3.90% on those inputs. That isn't a negotiating failure, it's arithmetic.

VENDOR Helcim's U.S. pricing lists interchange + 0.25% + 7c card present for $100K-500K monthly card volume, with no monthly fee. On this site's published pass-through assumption of 1.03% + $0.178 card present, that's 1.28% + $0.248. These effective rates are DERIVED, using the same formula:

Average card-present ticketHelcim $100K-500K band, effective
$252.27%
$501.78%
$1001.53%

That's a model. Your card mix can differ. Compare your statement at the same ticket and channel; add other fees.

The volume trap: At low volume, a handful of chargebacks can spike your ratio above network thresholds. A merchant doing 500 transactions/month only needs 5 chargebacks to hit 1.0%. See network program thresholds for the exact numbers.

That ratio alone won't put you in the Visa or Mastercard programs above. Visa's also needs 1,500 fraud reports and disputes in the month, and its merchant test applies when your acquirer isn't Above Standard or Excessive. Mastercard's needs 100 chargebacks. Amex is different: its US fee can apply after a location's monthly chargebacks minus reversals exceed 1% of its sales minus credits for three straight months, with no count floor. Exactly 1.0% doesn't cross that line. Your processor can act sooner than any of them.


How to Use These Benchmarks​

Step 1: Establish Your Baseline​

  • Choose a period covering your normal billing and sales cycle
  • Segment by CP/CNP, geography, method
  • Document as your baseline

Step 2: Compare to Benchmarks​

  • Does the source match your country, channel and definition?
  • Which of your own segments changed?
  • Where can you test a fix?

Start with a routine you can keep:

  • Weekly: Auth rate, fraud rate, chargeback ratio
  • Monthly: All metrics, segmented
  • Quarterly: Deep dive, re-baseline

Step 4: Set Alerts​

NOT PUBLISHED Universal alert cutoffs.

  • Auth: drops from your segment's normal range; check decline codes
  • Fraud: rises from baseline; allow for reporting lag
  • Chargebacks: approaches your limit; check counts too
  • Refunds: shifts from normal; check products, season and support issues

Where This Breaks​

  • Mixing CP and CNP. Never combine in single number.
  • Seasonality. Holiday, promo weeks skew baselines. Compare like periods.
  • High-risk MCCs. Travel, gaming and crypto need their own bands. Ask your processor for a comparison.
  • International traffic. Separate it from domestic traffic. Get a local acquirer before judging.
  • Low volume. Small sample sizes create noise. Read the counts beside the rate; see the volume trap above.

Do next​

Look up​

Deeper​

Establishing your baseline?

Comparing to industry?

Improving metrics?

Something wrong on this page? Email matt at paymentsandrisk.com and say what needs fixing.