How is extracted document data validated?

Validation is what separates raw OCR output from data a business can actually trust and act on, and it happens through several layers rather than a single check.

Check-digit validation applies specifically to MRZ data, where several fields (document number, date of birth, expiry date) are followed by a digit calculated using a defined ICAO algorithm. Recalculating that digit from the extracted data and comparing it to what's printed confirms internal consistency and catches a meaningful category of misreads or tampering without needing any external database lookup.

Cross-source validation compares data extracted from different parts of the same document, MRZ against visual zone, or either of those against barcode or chip data where available. Because these sources are printed or encoded independently during the document's manufacture, a genuine document should show identical information across all of them for overlapping fields like name and date of birth.

A mismatch is a meaningful signal, whether it turns out to be a scanning error or something more concerning.

Format and logic validation checks whether extracted data conforms to what's structurally expected: does the date of birth fall in a plausible range, does the document number match the expected pattern and length for that document type and issuing authority, is the expiry date actually after the issue date, and so on. This kind of check catches nonsensical or malformed data even without a corresponding check digit to verify against.

Confidence scoring is common in modern OCR systems, where each extracted field comes with a numerical confidence level reflecting how certain the underlying model is about that particular reading. Low-confidence fields can be flagged for manual review rather than accepted automatically, giving a business a practical way to route uncertain cases to a human without needing to review every single scan.

Taken together, these layers mean "extraction" and "validation" aren't really separate steps in practice. A well-designed system runs validation checks continuously as part of the extraction process itself, rather than treating extraction as complete before validation begins.

ScanDoc applies all of these validation layers, check digits, cross-source comparison, format checks, and confidence scoring, as a standard part of its data extraction process, aiming to give businesses data they can act on directly rather than raw OCR output that still needs independent verification.