PingOne

PingOne Verify and data-based verification

Data-based verification in PingOne Verify uses user-provided data, such as name, date of birth, and address, and trusted data sources (including credit bureaus and government databases) to validate a user’s identity. Data-based verification provides organizations with seamless validation to ensure adherence to security standards and regulations. Learn more in Creating a verify policy.

What is data-based verification?

Data-based verification validates a user’s identity by comparing personal information submitted by users with trusted data sources through matching algorithms.

Common sources include:

  • Credit bureaus

  • Government databases

  • Telecom and utility records

  • Identity graphs

The data-based verification process typically includes:

  • Data input: The user provides personal data.

  • Data matching: PingOne Verify checks its sources to find a matching profile or record.

  • Verification outcome: When you configure a verify policy using data-based verification, PingOne Verify assesses whether fraud or risk is associated with the user. PingOne Verify provides a match score or a pass or fail determination based on the strength of the match that’s aligned with the configurable thresholds (low, medium, high).

Unlike document-based checks, this process is often completed in real time with minimal user friction. Learn more in Creating a verify policy.

Progressive identity verification step

Data-based verification is more effective when used early in a multi-layered identity verification flow as an easy checkpoint, before thorough steps like document capture or biometric verification are initiated.

The following is an example onboarding flow with progressive steps:

  1. Data-based verification: PingOne Verify validates user-provided data against authoritative sources, returning confidence scores, match results, and potentially additional verified attributes (such as phone type, email domain, and identity confidence level) to enhance user profiles.

  2. Risk evaluation: When creating a PingOne Verify policy using data-based verification, configurable thresholds provide the following risk evaluations:

    • Low risk or strong match: Proceed with onboarding.

    • Moderate risk: Request additional data or passive signals (such as device reputation, geolocation, and so on).

    • High risk or no match: Escalate to document-based identity verification.

  3. Document-based verification (optional): PingOne Verify collects and validates a government-issued ID, performs biometric liveness detection and face match, and cross-checks extracted document data with data-based results to enhance assurance. Use this verification when risk evaluation returns a high risk, or no match is found.

This progressive, risk-based approach ensures low-friction onboarding for trusted users while preserving strong defenses against fraud and identity spoofing.

Complementing document-based verification

While either verification method can be used independently, combining data-based verification and document-based verification provides stronger, layered identity assurance. These verification methods use different verification signals.

Data-based verification

Confirms knowledge-based attributes and helps prevent synthetic identity fraud by validating the user’s existence and verifiable presence in trusted records.

Document-based verification

Confirms an individual’s possession of a unique item (mobile phone, hardware tokens, security keys) by verifying the authenticity of an identity documentation and ensures the user matches the photo using biometric checks.

Benefits of combining both verification methods

When implemented together, data-based verification and document-based verification offer a powerful, layered approach to identity proofing. Their combination addresses a broader spectrum of risks while enabling higher levels of assurance.

Combining both verification methods offers:

Broader signal validation

Organizations can validate both the identity data and the person presenting it.

Data-based verification confirms that personal information matches real-world records in authoritative sources.

Document-based verification verifies the authenticity of a government-issued ID and confirms that the person presenting it matches the document photo using biometric comparison and liveness detection.

Enhanced fraud protection

  • Stops synthetic identities: Data-based verification relies on trusted sources to confirm that the individual exists in legitimate systems, making it difficult for fabricated personas to pass.

  • Detects forged documents: Document-based verification uses image analysis and validation techniques to identify altered, expired, or fake IDs.

  • Prevents impersonation: With biometric face matching and liveness checks, document-based verification ensures the person presenting the document is its rightful holder. When this is cross-checked against verified identity data, it becomes much harder to succeed with stolen or borrowed identities.

Higher assurance and compliance

Combining both methods makes it possible to achieve compliance with strict identity assurance frameworks, such as NIST Identity Assurance Level 2 (IAL2).