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Stop emerging card attacks while improving approval quality
DataVisor adds device, behavioral, merchant, and network context to every authorization and pairs known-pattern models with unsupervised detection—so emerging attacks surface earlier and legitimate transactions face fewer unnecessary declines.
See context-rich card decisions in action.
What you can accomplish with DataVisor
Detect known, emerging, and coordinated attacks
Pair known-pattern detection with unsupervised machine learning to catch new attack patterns early.
Approve with greater confidence
Improve approval quality with context-rich risk decisions.
Route every transaction by policy
Approve trusted activity, decline clear fraud, step up, or investigate based on portfolio and channel policy.
Approve more good transactions with richer context
Real-time transaction scoring, rules, supervised and unsupervised machine learning, dEdge device and behavioral signals, Knowledge Graph relationships, identity and account context, and case workflows.
From authorization request to decision
Ingest card, merchant, customer, account, device, and session signals.
Compute behavioral, velocity, reputation, and network features.
Evaluate multiple detection layers in a single strategy.
Return approve, decline, step-up, review, or another action and retain the decision trace.
See a card decision in full context
Follow a card-not-present or digital-wallet event with device, merchant, account, behavioral, and network context—through the decision trace and case workflow.
Context-rich scoring across every channel
DataVisor combines transaction scoring with device, behavior, customer, merchant, account, and network context—and pairs known-pattern models with unsupervised detection for emerging attacks.
Protect every card channel
Connect card decisions across your ecosystem
Integrate issuer, processor, merchant, payment, identity, device, customer, and case-management systems through APIs and postbacks—powered by dEdge, Knowledge Graph, Rules & Features, machine learning, and Decisioning.
Common questions
What is card fraud?
Card fraud includes card-present and card-not-present fraud, stolen credentials, card testing, BIN enumeration, counterfeit or cloned cards, digital-wallet abuse, and coordinated attacks.
Does DataVisor meet card authorization latency requirements?
Yes. DataVisor makes real-time decisions designed for authorization speed.
How does DataVisor improve approval rates?
By adding device, behavior, customer, merchant, and network context to every decision, DataVisor separates legitimate activity from fraud more precisely—reducing false declines.
Grow approvals while reducing fraud
See a card decision built around your portfolio, payment channels, approval-rate goals, and operational workflow.