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Build every decision on a fuller view of the customer
Unify identity, device, behavioral, transaction, account, network, velocity, and third-party signals into a connected risk view. DataVisor gives strategies more context to identify fraud while reducing unnecessary friction for trusted customers.
Connect every signal into one risk picture
Combine identity, live device and behavioral context, history, and third-party intelligence so strategies see more than a point-in-time check.
Bring the attributes that define the customer into the decision
Use names, addresses, phone numbers, emails, tax IDs, payment identifiers, devices, IPs, and other identity attributes as part of the risk picture.
See what is happening around the identity now
Combine device integrity, network, behavioral, automation, and session signals with account and transaction context to detect changes that static identity data can miss.
Evaluate the event against what came before
Use historical activity, account context, transaction behavior, velocity, and prior risk intelligence to understand whether the current event fits the customer's established pattern.
Bring third-party risk signals into the same context
Incorporate supported identity and risk providers so external intelligence can contribute to rules, models, and decisions alongside DataVisor-native signals.
The risk profile behind every decision
Connect identity attributes, device intelligence, behavioral signals, and transaction activity to maintain risk context across the customer lifecycle, from onboarding and login through transactions and investigations.
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Turn raw signals into connected risk context
Associate incoming signals with the relevant entity.
Enrich and derive risk features from those signals.
Make the intelligence available to rules and models.
Carry that context into decisions and investigations.
Keep context connected across the lifecycle
DataVisor brings identity, device, behavior, transaction, network, and relationship intelligence into a common decision environment so teams can evaluate the customer with more than a point-in-time identity check.
Strengthen risk decisions across the customer lifecycle
Apply connected risk signals to onboarding, account takeover, login risk, card and payment activity, ACH/wire, scams, mule detection, and investigations.
Tie richer context to better outcomes
Richer signal coverage gives strategies more context to catch fraud earlier while cutting down on false positives and manual review.
Make every detection layer smarter with shared signals
Feed Identity & Risk Signals into Real-Time Decisioning, Rules & Features, supervised and unsupervised ML, dEdge, Knowledge Graph, Fraud Pattern Intelligence, and Case Management.
Keep risk context governed and resilient
Maintain visibility into where risk signals originate, how they contribute to decisions, and how they change over time. Govern access and data lineage while keeping decisioning resilient when individual data sources are delayed or unavailable.
- Signal provenance and lineage tracking
- Governed access and privacy protections
- Handling of conflicting signals across sources
- Resilience when third-party data is unavailable
Common questions
What types of risk signals can DataVisor use?
DataVisor can combine identity, device, behavioral, transaction, account, network, velocity, historical, and supported third-party risk signals.
Can DataVisor use third-party identity or risk data?
Yes, where integrated. Third-party signals can enrich the risk context used by rules, models, and decision strategies.
How does DataVisor reduce false positives with more signals?
Richer context allows strategies to evaluate combinations of identity, behavior, device, history, and relationships instead of relying on isolated indicators that may be ambiguous on their own.
Build a fuller risk picture
Walk through how DataVisor combines signals across the customer lifecycle and turns them into decision-ready intelligence.