Non-Identity Document Verification for Identity Workflows

Not every customer can present a government-issued identity document. Several categories of organization regularly encounter users who cannot complete a standard document-based identity workflow:

• Financial inclusion initiatives serving under-documented and underbanked populations.
• Immigration and refugee services.
• Gig economy onboarding.
• Services for young adults and populations in regions with limited ID infrastructure.

Even among customers who hold government IDs, many verification scenarios require additional evidence beyond identity. This includes proof of address, employment authorization, income documentation, medical records, insurance coverage, professional licensure, or immigration status.

Organizations running identity workflows in these contexts need verification capabilities that extend beyond passports, national IDs, and driver’s licenses. Each non-identity document has its own formats, issuing authorities, security features, and fraud patterns. Organizations must validate authenticity, extract relevant data, and integrate findings into the identity decision with a regulatory-compliant audit trail. AI-generated document fraud is compounding the challenge, with synthetic bank statements, pay stubs, utility bills, and other financial documents becoming easier to produce and harder to detect through manual review or rules-based tools.

Daon’s identity verification workflow validates not only passports, national IDs, and driver’s licenses, but also a wide range of supporting and alternative documents:

• Bank statements, utility bills, pay stubs, and tax documents.
• Loan applications and other financial documents.
• Employment authorization documents.
• Medical records and insurance cards.
• Professional licenses.
• Immigration documents.
• Other attestable evidence from any global source.

Daon applies forensic-level analysis to each document, evaluating more than 350 fraud indicators per document and returning results in seconds. The analysis includes:

• Font anomaly detection against the document’s expected typography.
• Metadata and software history inspection (creation software, modification timestamps, author).
• Structural integrity checks, barcode tracing, and version history analysis.
• Detection of AI-generated and template-based forgeries.
• Normalization of bank statements and similar financial documents into structured data equivalent to open banking output, giving organizations access to account activity, income patterns, and transaction history without requiring direct bank connectivity.

Data extracted from validated documents feeds both fraud signals and business workflows. Extracted values are matched against user-entered application data and authoritative external sources. Discrepancies between customer input and document data are a primary fraud signal for application fraud. The verified data then feeds downstream processes:

• KYC and customer due diligence.
• Affordability and income verification checks.
• Regulatory registry lookups (licenses, sanctions, watchlists).
• Eligibility decisioning for benefits, services, and entitlements.
• Source of Wealth and Source of Funds analysis for AML and CDD compliance.

The document results feed the identity decision alongside biometric face matching with presentation attack detection tested to ISO 30107-3 Level 2 standards, and any other signals in the workflow. Daon’s document recognition algorithm leverages machine learning, allowing new document types to be supported with as few as 20 samples, whether a regional utility bill, an employer-specific pay stub, a local tax form, or a document format that did not exist last quarter.

Financial inclusion programs, immigration services, gig economy platforms, and other organizations serving under-documented populations can verify identity using whatever documents customers can provide. Each document receives a full fraud analysis. Organizations requiring supporting documentation alongside identity verification can validate non-identity documents within the same xProof workflow. Customers complete a single identity journey regardless of how many documents are involved.