Generative AI for Payments: Merchant Support, Dispute Evidence, and Compliance

A payments company deploys a commercial AI tool for merchant support. Within weeks, several issues surface. The AI answers merchant questions about interchange rates by citing information that's outdated and doesn't reflect the current scheme fee schedule. The AI drafts chargeback representment responses that don't follow the compelling evidence structure Visa Claims Resolution and Mastercard MCBP each require — the responses get rejected because they don't match scheme requirements. The AI drafts SAR narratives that sound fluent but miss the specific typology language FinCEN examines. Each is a consequence of generic AI that doesn't know current scheme rules, compliance frameworks, or the specific language payments regulators expect — and each creates risk that outweighs the productivity gain.

Payments generative AI done right is grounded in current scheme rules, compliance frameworks, and approved content. Merchant support agents grounded in current pricing schedules, scheme fee changes, and the specific language compliance has approved for merchant communication. Chargeback representment drafting grounded in the compelling evidence structures Visa VCR and Mastercard MCBP define per reason code — with scheme-specific formatting and the evidence categories each scheme accepts. SAR narrative drafting grounded in FinCEN typology language and the specific patterns AML examinations review. Refusal patterns for rate guarantees, merchant approval decisions, and other content requiring specific human authority. With explainability for audit. Done with this discipline, generative AI reduces support and compliance workload. Done casually, it creates scheme chargeback rejections or BSA findings.