FairLedger turns your own transactional and pricing data into defensible, board-ready Consumer Duty evidence — reproducible on demand, without a consulting engagement.
FairLedger is a multi-tenant SaaS platform that auto-evidences the two quantitative Consumer Duty outcomes — Price & Value and Products & Services — for UK payment and e-money firms.
You upload your orders and published price lists. FairLedger validates every row, computes reproducible fair-value metrics, flags outliers against your own pricing, and assembles a board pack your compliance committee can defend line-by-line.
What used to be a quarterly consulting deliverable becomes a repeatable operational output — versioned, auditable, and produced from source data your firm already owns.
The FCA now tests whether firms can produce numerical fair-value evidence on demand. Boards need it. Auditors ask for it. Regulators expect it in the format FairLedger produces.
Fair-Price Gap, price dispersion, margin distribution and SKU-level outliers — computed from your data, not estimated.
Every metric ties back to the source batch, the row range, the price list version and the run timestamp. Nothing is a black box.
A one-click PDF board pack with headline metrics, outlier tables, methodology appendix and sign-off block.
Drop in orders and price-list CSVs. Row-by-row Zod validation preserves invalid rows for review.
Reproducible metric snapshots: revenue, margin, dispersion, Fair-Price Gap, top-SKU breakdown.
A tenant-scoped Evidence view with immutable snapshots and full audit trail across every run.
Export the branded board pack PDF, complete with methodology appendix and version stamp.
Owner / admin / member / viewer roles per workspace, with tenant-scoped row-level security on every table.
Storage is folder-isolated per tenant. Row-Level Security enforced in the database. No cross-tenant reads, ever.
Every analysis run writes a metric snapshot tied to the input batch — reproducible months later for audit.
Every ingest, delete, member change and evidence export is logged to a tamper-evident audit log.
Branded React-PDF output with headline metrics, Fair-Price Gap tables, top SKUs and a methodology appendix.
Revenue, margin, price dispersion, monthly time series and top-10 SKU breakdown — refreshed on every batch.
Authorised PIs producing fair-value evidence across merchant and consumer product lines.
EMIs evidencing pricing outcomes across cards, wallets and cross-border rails.
Programme managers evidencing outcomes for downstream branded programmes.
Second-line functions who need a defensible, repeatable evidencing operating model.
Any metric shown in the app can be re-derived from the exact batch and price list that produced it.
The methodology is documented, versioned and printed alongside every board pack — nothing is hidden.
Built to be run by compliance and finance teams — not to require a data science function.
A discovery call runs 30 minutes and covers your Consumer Duty evidencing approach, the FairLedger fit and the design partner terms.
