DEFEND WEBINAR | Agentic AI in Action: The Playbook from Best-Performing Fraud and Risk Teams
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 approved 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.
Show the risk profile behind the decision
Use an entity or identity profile, signal taxonomy, and lifecycle view to demonstrate how risk context accumulates from onboarding through login, transaction, and investigation.
attributes
behavior
fusion
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.
Keep risk context governed and resilient
Detail approved signal provenance, lineage, access controls, privacy protections, handling of conflicting signals, and resilience when third-party data is missing 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.