Total $ leaked through soft declines that retry / dunning could recover next month.
At a glance
Estimated dollar value of soft-decline revenue that retry / dunning / token-refresh could recover in the next period. The CFO-facing card that converts “we have a 5% decline rate” into “$X is on the table next month if we ship the right ops improvements”. Cross-platform: combines CS soft-decline value with the connected commerce platform’s repurchase rate and an estimated retry-success rate to project recoverable monthly revenue.
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 US-based enterprise online retailer running CyberSource for ecommerce + Adobe Commerce for the storefront. The 30-day window covers 14 Mar 26 to 12 Apr 26. Roughly 1.59M transaction attempts, 86,400 declines totalling 88 AOV. The decline-reason breakdown (filtered to soft declines only):
But not every customer would actually retry. The Adobe Commerce repurchase rate for this merchant is 0.42 (42% of customers who fail to complete a purchase attempt again within 30 days). Apply this:
- **820k against $140M monthly processing volume = 0.59%, on the lower end (suggesting their current dunning / retry / Account Updater coverage is decent but improvable).
expired_cardis the easiest win. Account Updater (Visa Account Updater, Mastercard ABU) automatically refreshes stored cards when reissued. Enrolment is a one-time setup; recovery rate runs 75-85%. For this merchant the recoverable onexpired_cardalone is 232k/period with no customer-side touchpoint required. This is “money on the table” the merchant can collect by enabling a service.insufficient_fundsis the next-highest-leverage. Payday-aligned retry schedules (typical: +5 days, +10 days, +15 days, with messaging adjusted for SSI / pension cohorts who pay mid-month) recover ~30% of insufficient-funds declines. The merchant’s current retry logic likely retries immediately + 24h after, which is suboptimal for this reason code. Re-tuning the retry schedule alone could recover 258k/period.do_not_honoris the largest bucket but lowest recovery. Issuer-side declines without explanation; recovery via dunning campaigns (“please update your payment method”) runs ~12%. This contributes the least-per-dollar to recoverable revenue but is still meaningful at scale (157k/period).- Cross-platform join is what makes this card honest. Without the commerce-side repurchase rate, the merchant might assume 100% of soft-declined customers would come back if asked, they wouldn’t. The 0.42 multiplier captures the real-world fact that 58% of customers who fail to complete a purchase don’t return; recoverable revenue is calculated against the 42% who do. This is the intellectual honesty that makes the number CFO-grade.
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 soft-decline data to the connected commerce platform’s repurchase rate. Operators investigating the underlying CS data should reference:- EBC2 → Reports → Conversion Detail Report, the daily transaction-level dump with reason codes. Sum
totalAmountfiltered to soft-decline reason codes for the soft-decline value side of the formula. - EBC2 → Reports → Decline Reason Report, reason-coded summary if enabled.
- The commerce-platform’s analytics for the repurchase-rate factor (Adobe Analytics, Shopify Analytics, BigCommerce Analytics).
Cross-connector reconciliation:
Known limitations / merchant FAQs
How accurate is the projection? For mature merchants, typically within ±20% of actual recovery the following month. The accuracy depends most on (a) calibration of retry-success-rate constants for the merchant’s specific issuer mix, and (b) seasonality in the repurchase rate. Override the manifest defaults with merchant-specific historical data for calibrated accuracy. Why include only soft declines? Hard declines (stolen_card, lost_card, pickup_card) are uncountable. Retrying them violates Visa / Mastercard rules and can trigger merchant-side enforcement. The card explicitly excludes them from the recoverable-value calculation.
My commerce platform isn’t connected, why is this card grayed out?
The formula needs the commerce-side repurchase rate. Without it, the calculation would assume 100% of customers come back, which is unrealistic and overstates recoverable revenue. Connect Adobe Commerce, BigCommerce, or Shopify to the same Vortex IQ workspace and the card lights up.
The card shows $820k recoverable but my finance team doesn’t trust it. How do I validate?
Run a quarter of the listed actions (Account Updater enrolment, payday-aligned retry, dunning campaign refresh) and measure actual recovered revenue against the projection. Most enterprises find the card lands within 15-25% of actual recovery; treat it as a directional figure for prioritisation, not a precise forecast for accounting.
Why does Account Updater have the highest recovery rate?
Because the underlying problem (expired_card) is mechanically resolvable without customer intervention. The card networks (Visa, Mastercard) maintain a service that automatically refreshes stored credentials when an issuer reissues a card. Enrolment is a one-time merchant setup; the recovery happens silently in the background. Compare to do_not_honor where there’s no mechanical fix, the issuer’s risk model has flagged the transaction and only changing the customer’s behaviour or relationship recovers the value.
Should I expect the recoverable number to grow as I scale?
Yes, linearly with processing volume. Soft-decline value scales with attempts; if processing volume grows 30% YoY, expect this card to grow ~30% YoY too. If the merchant ships ops improvements, the rate of growth slows or reverses (the merchant is now recovering more of the absorbed soft declines, leaving less in the “still recoverable” bucket).
Are 3DS-abandoned transactions counted as recoverable revenue?
No, this card is decline-driven. 3DS-abandoned transactions never authorised so don’t appear in the soft-decline taxonomy. The 3DS-side recoverable revenue lives in 3DS Friction Revenue Loss.
Does dunning recovery work for B2B / corporate cards?
Yes, often better than B2C. B2B / corporate cardholders typically have explicit billing contacts who respond to dunning emails reliably (vs B2C consumers who may ignore them). The recovery rate on B2B do_not_honor and insufficient_funds declines runs 30-45% via direct billing-contact email, vs 10-15% B2C.
My multi-currency global merchant, how does this work?
The card sums recoverable value per-currency at sync-time FX, then aggregates to the dashboard’s display currency for the headline number. The drilldown can show per-currency for finance teams reconciling against bank deposits.
Can I use this card for budgeting / quota-setting?
Yes, with caveats. The number is directional; treat as “if we ship the listed ops improvements, expect $X recovery”. For formal budgeting, use the historical recovery achieved (not the projection) and add growth assumptions. Most enterprise finance teams use this card for prioritising ops initiatives rather than for hard quota commitment.