The problem it solves

Payment gateways screen for card fraud in general — they don't know your business. Account takeovers on net-terms accounts, reseller abuse, sudden ship-to changes, and orders that are simply 'wrong for this customer' sail through generic rules. Meanwhile over-tight rules decline good customers.

What it does for your business

Learns each account's normal

Order size, cadence, product mix, ship-to patterns — anomalies are flagged relative to that account's own history, not a global threshold.

Catches what gateways miss

B2B-specific risks: compromised buyer logins, terms abuse, drop-ship anomalies, and quote manipulation — before fulfillment, not after chargeback.

Reduces false declines

Because the model knows your customers, it stops flagging your loyal accounts' big seasonal orders as suspicious — protecting revenue and relationships.

Routes, not just blocks

Scored orders flow to review queues with reasons; only the clearest cases auto-hold. Your team stays in control of the threshold.

How it works

Unsupervised anomaly models (isolation forest / autoencoder) over order, account, and payment features — designed to complement, not replace, your payment gateway's own screening.

What we need from you

Order history with outcomes (chargebacks, cancellations, holds if tracked), account master, and payment metadata from your gateway.

See Fraud & Anomaly Detection on data like yours

A 30-minute walkthrough on live sample data — including how the model is trained and validated.

Request a Demo