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14/09/2026 10:09 am
TL;DR: Chargeback rate is a useful internal signal, but processors and card networks can calculate it differently, so merchants may see mismatched figures even when the underlying dispute trend is the same, according to Signifyd. The real control problem is measurement discipline, because reducing disputes without suppressing approvals depends on segmenting the cause before changing fraud controls.
NHIMG editorial — based on content published by Signifyd: How to Calculate and Maintain Your Chargeback Rate in 2026
By the numbers:
- Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
- 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.
- 71% of NHIs are not rotated within recommended time frames, increasing the risk of compromise over time.
Questions worth separating out
Q: How should ecommerce teams calculate chargeback rate consistently?
A: Use one stable formula: chargebacks divided by total transactions, multiplied by 100.
Q: Why do processor and network chargeback figures often differ?
A: They often differ because each party may use a different time window, transaction set, or event definition.
Q: What do teams get wrong when chargeback rate rises?
A: The most common mistake is treating every increase as a fraud problem and responding with broader declines.
Practitioner guidance
- Define one internal chargeback formula Standardise the numerator, denominator, and reporting period so monthly trend lines remain comparable across channels and regions.
- Break disputes into source categories Segment chargebacks by fraud, first-party misuse, fulfillment, billing, and customer service before changing controls.
- Reconcile processor and network definitions Document which rate each partner reports, which transactions are included, and what threshold or monitoring rule applies.
What's in the full article
Signifyd's full post covers the operational detail this post intentionally leaves for the source:
- The exact chargeback formulas used by Visa, Mastercard, American Express, and Discover across different reporting windows.
- The worked example for calculating chargeback rate from transaction volume and dispute counts.
- The specific way VAMP and Mastercard ECP differ in denominator, timing, and event inclusion.
- The operational guidance for preserving approval rates while reducing chargebacks.
👉 Read Signifyd's guide to calculating and maintaining chargeback rate in 2026 →
Chargeback rate mismatch: what ecommerce teams need to measure?
Explore further
14/09/2026 10:10 am
Chargeback rate is a governance metric, not just a fraud metric. When a merchant does not define the denominator, reporting window, and event set precisely, the metric becomes operational noise. That weakens board reporting, threshold management, and trend analysis. For ecommerce teams, the governance task is to make chargeback rate comparable enough to support decisions, not merely visible enough to report.
A question worth separating out:
Q: How can merchants reduce chargebacks without hurting approvals?
A: They should improve decision precision instead of tightening every rule. That means separating risky transactions from legitimate ones using better identity, payment, behavioural, and network signals, then monitoring approval rate and false declines alongside dispute trends. The goal is fewer abusive or fraudulent charges, not fewer accepted customers.
👉 Read our full editorial: Chargeback rate accuracy depends on the metric you compare
