Data Matching

Data Matching is an approach where your system matches a CLEAR-verified user against your existing records using the attributes returned in the verification session. Instead of passing in your own identifier (as with Account Binding), you rely on comparing biographic and contact data.

How It Works

1. User completes verification in CLEAR’s hosted flow.
2. Your backend calls Get Verification Session with the verification_session.id.
3. CLEAR returns verified user attributes (traits) such as:
   • First name
   • Last name
   • Date of birth
   • Phone number
   • Email address
   • Government ID number (if configured)
4. Your system compares these attributes against your user database using your own matching algorithm.

Example Flow

1. User completes verification.
2. You retrieve the session:

{
  "verification_session_id": "verify_abc123",
  "status": "success",
  "traits": {
    "given_name": "Jane",
    "family_name": "Doe",
    "date_of_birth": "1990-04-12",
    "phone_number": "+1-415-555-1212",
    "email": "[email protected]"
  },
  "user_id": "psuid_xyz987"
}

3. Your system queries your database for records where:

• First name = Jane
• Last name = Doe
• Date of birth = 1990-04-12

4. Your matching algorithm scores the result and determines whether to:

• Link to an existing user profile
• Flag for manual review (if multiple matches or ambiguity)
• Create a new profile (if no match found)

Best Practices

Use multiple attributes:
Don’t match on name alone. Combine fields (name + DOB + phone) for higher confidence.

Handle fuzziness:
Implement tolerance for common variations (e.g., “Jon” vs. “John”, “Street” vs. “St”).

Log your decisions:
Store why a record was matched or created. This helps with auditing and debugging.

First-time match:

When linking a CLEAR user to a profile for the first time, store the CLEAR PSUID (user_id). After that, you can use PSUID for deterministic matches on future verifications.

When to Use Data Matching

Use Data Matching if:

• You already store strong biographic/contact data (name, DOB, phone, etc.).
• You want control over the matching algorithm (scoring, thresholds, manual review).
• You don’t have a stable identifier to pass via Account Binding, or you want a second layer of assurance.
• If you prefer CLEAR to handle the matching logic for you, consider the Biographic Matching API.