Understanding SSA's eCBSV API Matching Logic

The Social Security Administration's Electronic Consent Based Social Security Verification (eCBSV) API employs sophisticated matching algorithms to confirm identity information against SSA records. Our extensive testing has revealed key insights into how the system operates, though the exact logic remains proprietary.

Matching criteria

The eCBSV API evaluates four primary identity elements:

1. First name initial: Must match SSA records exactly.

2. Last name:

   • Uses Damerau-Levenshtein distance with a threshold of 1. This allows for:

     • One character substitution, insertion, or deletion.
     • One transposition of adjacent characters (counted as 1 edit, not 2).

   • Supports maiden names if registered with SSA.

   • (Important) Asymmetric matching for compound surnames:

     • SSA record "De La Rosa" won't match input "Rosa" (exceeds 1 edit).
     • SSA record "Rosa" will match input "De La Rosa" (contains full surname).

3. Social Security Number (SSN): Requires an exact match. Other tax IDs are not supported.

4. Date of Birth (DOB): Birth year must match exactly in most cases.

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Note:

Exception If the birth month matches, the year may be off by one.

Why this matters

The use of Damerau-Levenshtein distance for surname matching allows for more flexible and accurate comparisons, especially for names prone to transposition errors. This approach, combined with asymmetric matching for compound surnames, helps financial institutions establish a reasonable belief about customer identity while accommodating common variations and data entry errors.

Implementing eCBSV in your Socure integration

When integrating eCBSV with Socure, consider these matching nuances:

1. Prepare for potential mismatches with compound surnames.
2. Understand that transpositions (e.g., "Smith" vs "Smtih") are treated as a single edit.
3. Be aware that the system allows for slightly more variation in surnames than strict character-by-character comparison.

These insights can help optimize your verification process, reduce false negatives, and improve the user experience, especially for customers with complex surnames or those prone to minor typographical errors.