Can data extraction detect duplicate or reused document submissions?

Detecting duplicate or reused document submissions is a distinct capability from core data extraction, though it's a natural and common extension built on top of extracted data, and many identity verification platforms offer it as part of a broader fraud-prevention layer.

The basic mechanism relies on comparing extracted document data (document number, name, date of birth, and often a hash or fingerprint of the photo) against previous submissions stored in a business's own database. If a new submission's extracted data matches an existing record closely enough, the system can flag it as a potential duplicate, which might indicate someone attempting to create multiple accounts using the same identity, or, in more concerning cases, someone attempting to use a stolen or shared document across multiple fraudulent applications.

This kind of check is generally the business's responsibility to implement using extracted data, rather than something a data extraction vendor performs independently, since it requires access to the business's own historical record of previous submissions, which a scanning vendor processing a single document in isolation typically doesn't have visibility into unless the business specifically integrates this check.

Some more comprehensive identity verification platforms do offer duplicate-detection as a built-in feature, maintaining a database of previously processed documents (often anonymized or hashed for privacy) across their broader customer base, which can catch attempts to reuse the same document across entirely different businesses using the same platform, not just within a single business's own records.

Photo-based duplicate detection adds another layer, comparing extracted facial images across submissions using facial recognition techniques, which can catch cases where the same person is attempting multiple submissions using different document numbers, or conversely, catch mismatched cases where the same document number appears with different faces across submissions.

ScanDoc's data extraction provides the structured document data and photo needed to build this kind of duplicate-detection logic within a business's own systems, and businesses working with ScanDoc can implement matching against their own historical records using the consistent, structured fields the extraction process returns.