Face Search
Face Search is a powerful feature that allows you to search for a specific face across all your approved identity verification sessions. This capability helps identify duplicate accounts, prevent fraud, and enhance your security measures.
Automatic Face Search Integration
Face Search is automatically performed during liveness checks in verification sessions to detect duplicate users and check against blocklisted faces.
Automatic Duplicate Detection
When a user completes a liveness check during identity verification:
- Their facial biometrics are automatically compared against all previously verified users
- The system identifies potential duplicate accounts based on facial similarity
- Matches are flagged according to your configured similarity thresholds
- You can review and take action on potential duplicate users
Blocklist Integration
Face Search seamlessly integrates with the blocklist feature:
- During verification, faces are automatically checked against your blocklist
- If a match to a blocklisted face is found, the verification is automatically declined
- This prevents previously identified problematic users from creating new accounts
- Helps maintain the integrity of your verification process
API Access
Face Search functionality is also available through our API, allowing you to:
- Programmatically submit face searches
- Integrate face matching capabilities into your own applications
- Build custom fraud detection workflows
- Create automated systems for duplicate detection
Key Features
- High Accuracy: Advanced biometric algorithms provide reliable match results
- Configurable Thresholds: Customize match sensitivity based on your risk tolerance
- Comprehensive Scanning: Search across all your verified users
- Rapid Results: Process searches quickly even with large user databases
- Privacy-Focused: All processing happens within your secure environment
Configurable Thresholds
You can customize search sensitivity by setting different thresholds for similarity scores:
These thresholds can be adjusted based on your risk tolerance and security requirements.
How It Works
Face Extraction
When a search is initiated, the system:
- Extracts facial features from the reference image
- Normalizes the facial data for consistent comparison
- Validates image quality and facial clarity
- Creates a mathematical vector representation
Comparison Algorithm
The system then:
- Accesses your database of approved verification sessions
- Compares the reference facial vector against stored vectors
- Employs advanced neural network architecture
- Optimizes for both speed and accuracy
Similarity Scoring
For each comparison, the system:
- Generates a similarity percentage (0-100%)
- Uses multiple points of comparison for accuracy
- Applies your configured match thresholds
- Ranks potential matches by similarity score
Results Delivery
Finally, the system:
- Returns a ranked list of potential matches
- Provides supporting verification data
- Includes similarity scores for each match
- Makes match images available for review
Similarity Percentage
The similarity percentage is the core metric used to determine potential matches:
- High percentage (typically 90% and above): Indicates a strong likelihood that the faces belong to the same person.
- Medium percentage (70-89%): Suggests possible matches that may require further review.
- Low percentage (below 70%): Likely indicates different individuals.
The exact threshold for what constitutes a "match" can be configured based on your security requirements. Increasing the threshold reduces false positives but may increase false negatives.
Use Cases
- Fraud Prevention: Identify users attempting to create multiple accounts
- Enhanced KYC: Add an additional layer of verification to your KYC process
- Regulatory Compliance: Meet requirements for detecting duplicate accounts
- Access Control: Verify user authenticity for high-security areas
- Law Enforcement: Assist authorized agencies in identifying persons of interest