Card fraud prevention
Score every card transaction in under 50ms. Catch card-not-present fraud, stolen credentials and synthetic identities before authorization, without adding friction for legitimate customers.
- Authorization decisions in under 50ms
- Card-not-present and card-present fraud
- Synthetic identity recognition
- Risk-based step-up authentication
- Event
- AUTH 58C1-E2
- Channel
- Card not present
- Amount
- $1,240.00
Why it was flagged
- Card used on a device new to this cardholderDevice
- Billing and shipping countries differContext
- Device recently linked to card testingDevice
- Merchant type this cardholder has never usedBehavior
A 3-D Secure challenge is requested instead of a hard decline.
- <50ms
- Authorization decisions, scored before the transaction completes.
- 97%
- Fraud detection rate.
- 75%
- Fewer false positives, so fewer good customers are declined.
- One model
- Online, in-store and recurring payments scored the same way.
Models that adapt as card fraud changes
Machine learning models retrain on new fraud patterns and analyst outcomes, so protection keeps up without manual rule tuning.
Behavioral profiling
Compare each transaction with the cardholder's normal spending, devices and locations to surface anomalies.
Real-time scoring
Every transaction is scored and decided in milliseconds, at the point of authorization.
Synthetic identity detection
Spot identities built from a mix of real and fabricated data before they build credit and cash out.
Risk-based authentication
Trigger step-up checks such as 3-D Secure only when the risk warrants it, so low-risk checkouts stay frictionless.
Approve more good customers
Stop trading conversion for security. Vyndarix gives you the evidence to approve confidently and challenge only when it matters.
- 75% fewer false positives
- Decisions in under 50ms
- No manual rule maintenance
- Continuous model updates
- Reasons attached to every decision
- Chargeback outcomes fed back into models
How a card decision works
- 1
Authorization request arrives
Card, device and merchant data come from your processor or gateway.
- 2
Signals are scored
Behavioral, device and network signals combine into one risk score.
- 3
A decision is returned
Approve, step up with 3-D Secure, or decline, with the reasons attached.
- 4
Outcomes teach the model
Chargebacks and analyst dispositions feed back into training.
Questions about card fraud prevention
What is card-not-present (CNP) fraud?
Card-not-present fraud occurs when stolen card details are used for transactions where the physical card isn't required, such as online purchases, phone orders, or recurring payments.
How fast can transactions be scored for fraud?
Vyndarix scores transactions in under 50ms, so fraud decisions happen at the point of authorization without slowing checkout.
What is synthetic identity fraud?
Synthetic identity fraud involves creating fake identities using a combination of real and fabricated information. These identities are used to open accounts and commit fraud over time.
Stop card fraud without blocking good customers
See how Vyndarix scores card transactions in under 50ms and explains every decision it makes.