Fraud and money laundering hide in the gaps between payment providers. Crosswatch joins Adyen, Stripe, Mollie and the rest into one risk picture, and its AI triages what no single PSP can see.
| Time | PSP | Customer | Method | Amount | Risk |
|---|
Watching…
Overnight, Crosswatch AI closes the obvious false positives with a written reason, links accounts across PSPs, spots patterns none of your rules cover and tunes the rules you have. In the morning your team gets a short list, ranked by risk.
Purchases paid by card on Adyen are being refunded to new iDEAL accounts through Mollie. 31 customers, most created in the last 10 days. None of your current rules covers it.
You route payments over several PSPs for cost and uptime. Fraudsters spread their attempts the same way, so each PSP sees too little to act.
A device tries 11 stolen cards in 38 minutes, spread over three PSPs so none of them hits its own limit.
Twelve detections out of the box, each tuned to work across PSPs. Add your own rules and back-test them on a year of history before they go live.
Many cards tried from one device or IP in a short window, usually small amounts.
Attempts are spread so each PSP stays under its own limit.
device fingerprintIPcard BINdecline codesConnect each PSP the way it already exports data, send events from your checkout, and get a score back before you capture the payment.
{
"event": "payment.authorise",
"psp": "adyen",
"amount": { "value": 4999, "currency": "EUR" },
"customer": { "id": "c_48120", "email_hash": "9f2c…" },
"device": { "id": "d_7f21", "ip": "85.x.x.14" },
"card": { "bin": "535522", "last4": "4417" }
}{
"score": 92,
"decision": "review",
"reasons": [
"device_seen_on_3_psps",
"11_cards_in_38_min",
"declines_above_baseline"
],
"case_id": "CW-2041"
}Your PSPs, flows and current controls mapped with your compliance lead.
PSPs connected, 12 months loaded, customers resolved across rails.
Detections back-tested on your history. See what would have fired.
Live scoring next to your current process, without decisions.
Alerts, cases and reporting on, with your team trained.
The EU AML Regulation applies from July 2027 and raises the bar on monitoring, record-keeping and reporting. Crosswatch keeps the evidence for every decision: what you saw, when, and what you did.
New detections, connectors and list sources every week. Rules you already run never change without your approval.
Flags refunds paid out to a different PSP or account than the original payment.
EU and UN sanctions lists are now checked every 15 minutes, and every customer is re-screened when a list changes.
Suspicious transaction reports export in the goAML format used by the Dutch FIU and many others.
Payments, disputes and payouts from Checkout.com now stream in real time.
Processed and stored in Frankfurt and Amsterdam, never outside the EEA.
Every alert and AI decision shows its reasons and evidence.
Only your team can block, report or approve.
Leave any time; your data is deleted within 30 days, with a certificate.
Every payments team I spoke to had the same blind spot: each PSP sees its own slice, and the patterns that matter only show up across all of them.
Crosswatch is the view that should have existed from the start.
Any PSP with an API or settlement files, including acquirers, wallets, bank-transfer providers and BNPL. Most connections are live within a day.
Keep them. Crosswatch sits on top and adds what no single PSP can: the view across all of them, in one profile per customer.
It scores and alerts in real time, and can feed decisions back to your checkout. Final calls on cases and reports stay with your team.
Crosswatch drafts the report from the case file, with the transactions and evidence attached. Your compliance officer reviews and files it.
Merchants and marketplaces using several PSPs, platforms that pay out to sellers, and PSPs that want to see across their sub-merchants.