Set Up Identity Fields for ID Cards and Passports

What this guide helps you do

This guide shows how to configure an ID card parser in PerfectParser, define identity fields, run a test batch, and export verification data. Leave the AI prompt blank on the first pass unless you need tighter mapping to specific document zones on licenses or passports.

Why ID cards are hard to parse

Identity documents combine a visual inspection zone (name, photo, dates printed on the front) with a machine-readable zone (MRZ) on passports and many national IDs. The two zones can disagree — a typo in the visual zone vs the MRZ — and your schema should capture the fields your compliance workflow treats as authoritative. Issue date and expiry date sit near each other and are frequently swapped during auto-detect. Photos and holographic overlays cause glare that obscures document numbers on phone-captured images. Driver's licenses from different US states use entirely different layouts with no shared field positions. International passports add nationality and issuing authority in non-English scripts. Expiry date format varies (DD/MM/YYYY vs MM/DD/YYYY), so storing dates as Text preserves the printed format for downstream validation rules.

Recommended Fields

We suggest configuring the following schema fields for your ID & Passport Parser to capture all essential compliance data.

AI Prompt (Optional)

Use this only when you want to guide auto-detect toward a specific set of fields.

If you want PerfectParser to discover additional fields on its own, leave the AI Prompt (Optional) box blank for the first pass, review the detected schema, then add a prompt only if you need tighter consistency.

When you do use a prompt, copy and paste the following instructions into the AI Prompt (Optional) field during setup:

Extract the document type, unique document number, holder's full name, date of birth, nationality, issue date, expiration date, and issuing authority.

Set up this parser in the dashboard

Create a parser

Go to Parsers → New Parser in the dashboard. Give it a name like "ID Card Parser" and optionally select the document category.

Upload a sample document

Drag and drop a representative ID document (PDF, PNG, or JPEG). Use the document type and image quality typical of your KYC intake — the AI uses it to learn field placement.

Detect fields or use standard fields

Paste the AI Prompt from the section above into the AI Prompt (Optional) box if you want tighter field mapping, then click Auto-Detect. To discover more fields automatically, leave the prompt blank and click Auto-Detect. Or skip auto-detect and add fields manually using the Recommended Fields table above.

Review and save your schema

Check that issue_date and expiry_date are separate fields and not swapped. Confirm document_number is Text to preserve alphanumeric passport numbers. Click Save.

Run a test batch

Navigate to Bulk Extraction, choose how your files are organised, upload a small test set of ID images, and click Extract All Files. Review the results in Batch History and export to CSV or Excel.

Common mistakes

• Swapping issue_date and expiry_date because both appear as date fields in the header region.
• Using a glare-free scan as the sample when user uploads are phone photos with reflection on the laminate.
• Storing document_number as Number — passport and license numbers often contain letters.
• Ignoring MRZ vs visual zone discrepancies — add field descriptions noting which zone your workflow prioritises.

Next steps

• Create a Parser guide
• Bulk Extraction guide
• Export Results guide