Challenges with Existing Solutions
- Inability to detect blurred, glared, partial, and obscured ID images can lead to application rejection and delays user onboarding.
- Inability to assess the quality of the photo of face on the ID may lead to inaccuracies, potentially allowing manipulated submissions.
- Verifying IDs without confirming face presence disrupts the face match process and creates vulnerabilities for potential fraudulent entries.
- Absence of ID liveness checks makes it challenging to ensure the authenticity of the presented identification.
What We Offer
- Provide instant user feedback during document capture for issues like blur, glare, partial, or obscured ID, minimizing the chances of application rejection.
- Ensure the face quality on the ID is optimal for accurate face matching with the selfie, reducing the risk of identity theft.
- Enhance security with ID liveness checks, confirming the authenticity of presented identification.
Input and Output
Integration Made Easy
100+ API integrations supported across regions and industries via ONE SDK
Integrate in less than a week
Dedicated customer support for smooth integration
Build End-to-end Journeys with HyperVerge ONE
Build end-to-end financial product onboarding journeys with ease
Configure user onboarding workflows and UI/UX without code.
Set automated fallback options to prevent user drop-offs during downtimes
Get analytics on conversion rates and optimize the friction points
Explore our Integrations Marketplace
Visit Page >Frequently
asked questions
What functionalities does HyperVerge's ID Card OCR Quality Checks offer?
How does this functionality contribute to reducing application rejection rates?
Is this module effective in preventing identity theft?