The Real Cost of a High Decline Rate (It's Bigger Than You Think)

When merchants think about reducing payment costs, they almost always start with processing fees — the visible line items on a monthly statement. Getting your acquiring markup from 0.25% to 0.15% feels like a win. And it is. But it's almost never where the biggest money is.

The far larger commercial opportunity — and the one consistently under-prioritised — is approval rate optimisation. A 5% improvement in approval rate typically delivers 3–5 times more incremental revenue than a 10 basis point reduction in processing fees. The maths is almost always that stark.

Defining the Problem: Hard vs Soft Declines

Not all declines are equal. A hard decline means the issuing bank has definitively rejected the transaction — the card is blocked, the account is closed, or the transaction has been flagged as fraudulent. These are genuine stops.

A soft decline means the issuing bank has declined the transaction for a reason that may be transient: insufficient funds at that moment, a security threshold triggered by an unusual pattern, or the issuer not recognising the merchant descriptor. Soft declines are where the opportunity sits — and where most merchants leak significant revenue without knowing it.

Running the Numbers: What a 5% False Decline Rate Actually Costs

Let's model a real scenario. A subscription business processing £20M in annual card volume with an 87% approval rate — 13% of attempted transactions are declined. Industry data suggests that for well-managed subscription businesses, a realistic false decline rate within those declines is 30–40%.

The direct revenue impact is significant. But the LTV impact is typically where the real cost sits — a customer who experiences a payment failure is far more likely to cancel than one who doesn't, even if the payment is eventually recovered.

Why Approval Rates Are Lower Than They Should Be

The causes of avoidable declines vary, but the most common we see across merchant clients are:

• No intelligent retry logic: When a transaction is soft-declined, many merchants simply present it again — same time, same acquirer, same parameters. Issuers see this as suspicious behaviour and decline again. Smart retry means waiting, varying the route, and timing retries around when the customer is most likely to have funds (e.g. payday).
• Single acquirer with a weak BIN acceptance profile: Different acquirers have different relationships with different issuers. A transaction declined by acquirer A may well be approved by acquirer B for the same card.
• Poorly configured 3DS: 3DS (Strong Customer Authentication) is necessary, but badly calibrated 3DS challenge rates are a material driver of abandonment and soft declines. Frictionless 3DS — where the issuer authenticates silently — should be the target, and it requires working with your acquirer on RBA (Risk-Based Authentication) settings.
• Missing or poor merchant descriptor: Issuers decline transactions with unrecognised or suspicious merchant names. A clear, recognisable descriptor reduces issuer-side friction.
• No network tokenisation: Card-on-file transactions using raw PANs (card numbers) have consistently lower approval rates than those using network tokens (Visa Token Service, Mastercard MDES). The delta is often 2–4% on recurring transactions.

What Good Looks Like

For a UK subscription business processing primarily domestic consumer cards, a well-optimised approval rate should be above 92–94% for initial transactions and above 88–90% for recurring. If you're materially below these numbers, there is almost certainly a recoverable opportunity.

The starting point is always a decline reason code analysis — breaking down your declines by issuer response code to understand whether the primary driver is fraud prevention, insufficient funds, technical errors, or something else. Each category has different solutions, and treating them all the same is why most approval rate improvement projects underdeliver.