1. Approval Rate
Approval Rate (AR) is the percentage of authorization attempts approved by the cardholder’s bank, also known as the issuer.
Approval Rate = Approved authorizations / All authorization attempts × 100%
Approval Rate differs from Payment Success Rate. Approval Rate measures the success of bank authorizations, while Payment Success Rate reflects the outcome of the entire payment process.
Issuer declines
Common decline codes include do_not_honor, insufficient_funds and generic_decline.
A sharp increase in insufficient_funds may indicate problems with audience quality or recurring payments.
If do_not_honor increases, analyze geography, BIN, issuer, merchant category code (MCC), transaction amount and CIT/MIT. This code does not provide a specific reason for the decline.
For generic_decline, check the payment outcome to determine whether the decline came from the issuer or from Stripe’s payment controls.
Issuer fraud controls
Each issuer uses its own risk models.
For example, a customer usually makes purchases of €20–50 in Finland. A sudden online transaction for $150 with a foreign merchant may appear unusual to their bank.
Card and merchant geography
Approval Rate can depend on the relationship between:
- The customer’s country.
- The card’s country.
- The country of the Stripe account or acquiring bank.
For example, US customer + US card + US acquiring is typically a more natural payment route than US customer + US card + EU merchant or acquiring.
The second route may be treated as a cross-border transaction.
Cross-border payments are not necessarily declined. However, approval rates may be lower for certain issuers, BINs or business types.
BIN and issuer
The BIN, or Bank Identification Number, is the first part of the card number. It helps identify the issuing bank, country, card type and other characteristics.
The issuer is the bank that issued the customer’s card.
Some issuers may apply stricter controls to:
- Subscription businesses.
- Cross-border transactions.
- Certain merchant category codes.
- Recurring payments.
- Transactions of particular amounts.
- Specific merchants.
Customer-initiated and merchant-initiated transactions
CIT: Customer-Initiated Transaction
The customer actively starts the payment and can complete 3D Secure (3DS) authentication when required.
This gives the issuer more evidence that the payment is legitimate and may reduce its perceived risk.
MIT: Merchant-Initiated Transaction
The merchant initiates the charge without the customer’s active involvement, as with many recurring subscription payments. The customer cannot complete an interactive 3DS challenge during that unattended charge.
The issuer therefore relies more heavily on previous payment history, accurate recurring-payment data and its own risk model.
Analyze CIT and MIT separately because their decline patterns and underlying causes can differ.
2. Payment Success Rate
Payment Success Rate is the percentage of all payment attempts that ultimately complete successfully.
Payment Success Rate = Successful payments / All payment attempts × 100%
Payment Success Rate is broader than Approval Rate. It covers the entire process from the initial payment attempt to successful completion.
Example
Out of 1,000 payment attempts:
- 900 reach authorization.
- 810 receive issuer approval.
- 800 complete successfully.
Approval Rate = 810 / 900 × 100% = 90%
Payment Success Rate = 800 / 1,000 × 100% = 80%
Issuer approval
More issuer declines generally reduce both Approval Rate and Payment Success Rate.
Examples include increases in do_not_honor and insufficient_funds. For generic_decline, check whether the payment was declined by the issuer or blocked by Stripe.
3DS and authentication
A customer may fail to complete authentication because they:
- Close the authentication page.
- Do not approve the payment in their banking app.
- Enter an incorrect verification code.
- Abandon the process.
The payment may therefore fail even when there is no direct issuer decline.
Stripe Radar and fraud blocks
Stripe Radar can identify a payment as high risk and block it.
A blocked payment does not complete successfully, which reduces Payment Success Rate.
Technical errors
Integration issues, API errors, PaymentIntent errors or problems with checkout or the payment service provider (PSP) can prevent a payment from completing.
These failures may be unrelated to the customer’s bank.
Customer behavior
A customer may start checkout but leave before paying, abandon authentication or decide not to complete the purchase.
Whether these events reduce Payment Success Rate depends on how your analytics define a payment attempt. Use a consistent definition when comparing results.
3. Decline Rate
Decline Rate (DR) is the percentage of authorization attempts that are declined.
Decline Rate = Declined authorization attempts / All authorization attempts × 100%
A high Decline Rate alone does not explain the cause. Analyze decline codes, geography, BIN, issuer, CIT/MIT and changes over time.
Common decline codes
insufficient_funds: The card has insufficient funds.do_not_honor: The issuer declined the payment without providing a specific reason.generic_decline: A generic decline that may also reflect a block by Stripe Radar or Adaptive Acceptance.expired_card: The card has expired.incorrect_cvc: The card security code is incorrect.card_velocity_exceeded: The customer has exceeded the balance, credit limit or transaction amount limit available on the card.
Interpreting changes in decline patterns
A sharp increase in insufficient_funds, especially for MIT, may indicate problems with recurring collections.
An increase in do_not_honor requires deeper analysis because the issuer does not provide a precise explanation. Compare:
- Geography.
- BIN and issuer.
- CIT versus MIT.
- Transaction amount.
- Merchant category code.
Declines on recurring payments
Analyze customer-initiated and merchant-initiated payments separately.
MIT can have a higher Decline Rate because:
- The customer is not actively participating in the payment.
- The card may have insufficient funds.
- The card may have been replaced or blocked.
- The issuer may apply stricter controls to recurring transactions.
4. Fraud Rate and Stripe Radar
Fraud Rate measures the share of transactions identified as fraudulent or subsequently flagged for fraud.
Stripe Radar assesses transaction risk and can allow, review or block payments based on risk signals and configured rules.
Traffic quality
Fraud rates can vary significantly by traffic source, geography and audience.
If fraud increases after a new traffic source launches, compare results by source, campaign, geography and BIN, where those data are available.
Geography, BIN and issuer
Some countries, issuers or BIN ranges may account for a disproportionate share of fraudulent transactions.
Look beyond the overall Fraud Rate and compare:
- Geography.
- BIN.
- Issuer.
- Traffic source.
- Product.
Radar settings
More permissive rules may allow more payments to proceed and improve conversion. However, they may also allow more potentially fraudulent transactions through.
Stricter rules may reduce fraud but increase false positives, where legitimate customers are incorrectly blocked. This can reduce Payment Success Rate.
The objective is to balance conversion and risk.
5. Dispute Rate and Early Fraud Warnings
Dispute Rate
Dispute Rate is the share of payments that cardholders dispute through their bank.
A simplified formula is:
Dispute Rate = Disputed transactions / Successful transactions × 100%
Reporting periods and card-network formulas may differ.
A high Dispute Rate is a significant risk indicator for a payment account.
Fraud
A cardholder may not recognize a transaction and tell their bank:
“I didn’t make this purchase.”
This may become a fraud dispute.
Friendly fraud
Friendly fraud occurs when a customer makes a purchase but later disputes it through their bank.
For example, they may have forgotten about a subscription or failed to recognize the business name on their bank statement.
Statement descriptor
An unfamiliar name on a bank statement can increase the likelihood of a dispute.
The statement descriptor should help the customer recognize the business and understand the charge.
Subscriptions and cancellation
Subscription disputes may result from:
- Unclear trial terms.
- Unexpected automatic renewals.
- Difficulty canceling a subscription.
- Recurring charges the customer did not expect.
Early Fraud Warnings
An Early Fraud Warning (EFW) is a card-network warning that a payment has been reported as potentially fraudulent.
An EFW can arrive before a dispute, making it a useful signal for identifying problems earlier. However, it does not always precede or lead to a dispute.
A possible sequence is:
- A payment completes successfully.
- A fraud report generates an EFW.
- The payment may later become a dispute.
Why EFW monitoring matters
An increase in EFW may reveal a problem before it becomes visible in the Dispute Rate.
When EFW increases, compare:
- Geography.
- BIN.
- Product.
- Traffic source.
- CIT versus MIT.
- Merchant or Stripe account.
Example
Suppose the EFW rate rises from 0.2% to 0.8% after a new traffic source launches.
The next steps are to:
- Identify where the increase originated.
- Find the geography or campaign responsible.
- Limit the problematic source before it generates more disputes.
Fraud signals and EFW can provide an early indication of a problem, while the Dispute Rate shows disputes that have already occurred.