At a glance
Estimated dollar value of revenue lost specifically to 3DS challenge friction in the period. Cross-platform: combines CS 3DS abandon counts with the connected commerce platform’s AOV and an estimated abandon-to-lost-sale correlation percentage. The CFO-facing card for “what’s PSD2 / SCA actually costing us”, converts 3DS abandon rates into a dollar figure that justifies UX investment in saved-payment-method flows, smart routing, and frictionless-rate optimisation.
Calculation
Calculated automatically from your CyberSource data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A UK-based enterprise online fashion retailer running CyberSource for ecommerce + Adobe Commerce for the storefront. The 30-day window covers 14 Mar 26 to 12 Apr 26. Roughly 451,100 3DS challenges shown across UK + EU + global traffic; 122,400 of those were abandoned (27.13% abandon rate, see 3DS Challenge Abandon Rate). The factors:- £5.41M/period in 3DS friction loss is meaningful. PSD2 / SCA mandated 3DS in the UK + EU is genuinely costing the merchant ~£65M/year. Worth an annual VP-level conversation about where the merchant should invest to reduce the abandon rate.
- The 65% correlation factor is conservative. Industry data shows 60-75% of 3DS abandons are truly lost (the customer doesn’t come back via any path). The 65% default is a middle estimate; for fashion retailers with strong cart-recovery email programmes, actual recovery may be slightly better than 35% (so the friction loss is closer to £4.5M); for low-loyalty / commodity-product merchants, recovery is worse (so the loss is closer to £6.0M). Override the default with the merchant’s actual data for calibrated accuracy.
- The card pairs naturally with 3DS Challenge Abandon Rate. The abandon-rate card is the diagnostic; this card is the dollar quantification. For the same incident, abandon-rate goes up 1pp → this card goes up ~£200k/period (at this merchant’s volume + AOV). The £200k-per-percentage-point-of-abandon-reduction is the metric that justifies UX investments in saved-payment-method flows, smart routing, and frictionless-rate optimisation.
- Action plan with quantified ROI. Three improvements typically reduce 3DS abandon by 5-8pp combined, recovering 25-40% of this card’s value:
- Push to network-token saved flows (Apple Pay, Google Pay): 3DS happens at provisioning time, not at checkout. Estimated abandon reduction 2-3pp = £1.0-1.5M annual recovery.
- Smart routing for mobile-web (route to issuers with better mobile-challenge UX): 1-2pp reduction = £0.5-1.0M.
- Frictionless-rate optimisation via richer device-fingerprint data: 2-3pp reduction (more transactions go frictionless = fewer challenges = fewer abandons) = £1.0-1.5M.
- Geography-specific drilldown is critical. UK / EU traffic is PSD2-mandated; non-EU traffic is opt-in 3DS. Splitting the card by geography shows: UK / EU contributes ~85% of friction loss; non-EU only ~15%. The merchant can prioritise EU-specific UX investments and consider opt-out 3DS for non-mandated geographies above the AOV threshold for liability protection.
Sibling cards merchants should reference together
Reconciling against the vendor’s own dashboard
Where to look in CyberSource Business Center (EBC2): This card has no direct EBC2 counterpart, it’s a Vortex IQ derived figure that joins CS 3DS abandon counts to the connected commerce platform’s AOV. Operators investigating the underlying data should reference:- EBC2 → Decisions → Payer Authentication → Performance Reports, CyberSource’s 3DS Server performance dashboard.
- EBC2 → Reports → Payer Authentication Report, the daily 3DS-outcome dump.
- The commerce-platform’s analytics for the AOV factor.
Cross-connector reconciliation:
Known limitations / merchant FAQs
Why is the correlation factor 65% and not 100%? Because not every 3DS abandon is a truly lost sale. Industry data shows ~35% of abandons are absorbed by alternate paths: customer retries on a saved Apple Pay / Google Pay credential immediately (no 3DS challenge), or comes back via cart-recovery email and completes days later. The 65% factor isolates the truly-lost slice. For merchants with weaker post-abandon recovery flows, the correlation can run higher (70-80%); for merchants with strong saved-payment-method options, lower (50-60%). My PSD2 / SCA exposure is high. Can I opt out? Not for in-scope EU / UK transactions; PSD2 / SCA is regulatory. The lever is reducing how often customers see a challenge: (a) maximise frictionless rate via richer device-fingerprint data; (b) invoke TRA exemption for low-risk transactions; (c) invoke low-value exemption (under €30); (d) push to saved-payment-method flows where 3DS happened at provisioning. None of these is “opt out”; all reduce the challenge rate, which reduces this card’s value. My non-EU traffic is also flowing through 3DS. Why? Either: (a) merchant opt-in to 3DS for liability shift on potentially-fraudulent transactions; (b) the issuer requires 3DS regardless of regulatory regime (some Latin American, India, parts of Asia mandate 3DS); (c) the merchant’s gateway / orchestration layer is configured to invoke 3DS by default. For non-mandated geographies above the AOV threshold, 3DS-for-liability-shift can be net-positive (saving more on chargeback exposure than the friction loss costs); below, it’s net-negative. The number is huge. Is it really lost or is it just delayed? 65% genuinely lost; 35% delayed / recovered. This is the calibrated default. The merchant can validate by comparing this card’s monthly value to the commerce-side cart-recovery email programme’s actual recovered revenue. If the recovered revenue is meaningfully higher than 35% of this card’s value, the correlation factor should be lowered. If lower, raised. Does this card help me decide whether to invest in saved-payment-method flows? Yes, directly. Saved-payment-method flows (Apple Pay, Google Pay, network tokens) bypass per-transaction 3DS by handling authentication at provisioning time. Each percentage point of traffic shifted to saved-payment-method reduces this card’s value roughly proportionally (because those transactions don’t hit the 3DS challenge flow). For a merchant with £5M/period 3DS friction loss, shifting 30% of EU traffic to saved-payment-methods is worth ~£1.5M/period. Why doesn’t Stripe have an equivalent card? Stripe’s 3DS implementation is internal to itspayment_intents flow and the abandon data isn’t surfaced as cleanly as CyberSource’s /tss/v2/searches threeDSecureStatus field. Multi-acquirer merchants with both CS and Stripe should treat this CS card as the canonical 3DS-friction view across processors.
My multi-currency global merchant, does this card work?
Yes. The card sums abandon-count × per-currency-AOV separately, then aggregates to display currency at sync-time FX. The drilldown shows per-currency breakdown for finance-grade reporting.
How fast does this card refresh?
Daily. This is a trend / projection card, not real-time. For active-incident 3DS spikes use 3DS Failure Alert which fires in real-time on rate-of-change in success / abandon rates.
Can I exclude opt-in 3DS from the calculation?
Not in the default formula, but the manifest supports filtering by 3DS-mandate flag if the merchant tags their authentication flows. For most merchants the regulatory-mandated 3DS dominates the friction loss anyway, so the filter has small impact.
Is the correlation factor calibrated regionally?
Not by default; the 65% is global. Regional calibration is a manifest setting that some enterprise merchants enable, especially when they have very different cart-recovery effectiveness across geographies (UK / EU strong recovery, LATAM / India weaker).