GenAI - Enhancing AI-Based Identity Verification with Real-World Document Data

SUMMARY

Oprimes supported a leading identity management client in Switzerland by collecting and annotating real-world identity document data to train an AI verification system. The project involved 25 users and 500+ datasets across 27 document types. With strict compliance to GDPR and Swiss data privacy laws, the system’s fraud detection and document recognition capabilities saw marked improvements.

THE CHALLENGE

• Collecting high-quality images in varied lighting and angles.
• Ensuring diversity across 27 types of identity documents.
• Maintaining strict adherence to GDPR and Swiss privacy laws.
• Detecting fraudulent or tampered documents in real-world conditions.

SOLUTION

• Localized Participant Sourcing from within Switzerland.
• Real-World Data Collection across varied lighting, angles, and document conditions.
• Detailed Annotation & Validation of 500+ datasets by trained reviewers.
• GDPR-Compliant Workflow ensuring secure consent and data handling.
• Iterative AI Training Support with continuous feedback and refinements.

KEY OUTCOMES

• Improved document field extraction and recognition accuracy.
• Strengthened fraud detection through real-world training data.
• Generated valuable insights for further AI refinement.
• Set foundation for scalable, region-specific identity verification..