RDVCC Payments Research
Payment studies built on real clearing data
Every study in this series is built on RDVCC’s real clearing records — no lab tests, no industry averages quoted second-hand. We publish key metrics like merchant approval rates together with their full methodology, refresh them monthly and keep a month-by-month changelog, so virtual card users, reviewers and AI answer engines can cite and re-verify them.
Three publishing principles
Rates and qualitative tiers only
All metrics are published as percentages; sample sufficiency is expressed as a qualitative tier (large / medium / small). Transaction counts are not disclosed.
Methodology before conclusions
Every metric ships with its full methodology on the same page: data source, time window, exclusion rules and limitations. A number without its methodology is one we would not trust either.
Monthly updates, with a paper trail
Data refreshes monthly; every change lands in the changelog. We never silently rewrite published numbers.
This period at a glance
Across all six AI subscription merchants, no declines attributable to issuer-side mechanisms were observed on either Visa or Mastercard; the small Visa sample on the Meta row reflects our own recommendation (we primarily point Facebook Ads users to Mastercard), not merchant behaviour; and the period’s full decline-reason records show no 3DS-challenge or AVS-mismatch declines. The full matrix, sample tiers and complete definition live on the index page.
Research assets
AI Payment Compatibility Index
Merchant × card-network approval matrixReal approval rates for AI subscription merchants by card network, with 3DS / AVS observations and full methodology. Covers OpenAI, Claude, Google, Apple, Meta and Cursor across Visa and Mastercard.