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Identity Verification Settings

Control how strict the face match is during check-in. This compares the guest's selfie against their ID to decide whether they can continue self check-in or need staff assistance.

Where to Find It​

Settings → Security → Identity Verification

Guest & Staff Impact​

  • Guests: Stricter settings reduce fraud but can increase check-in interruptions if the match fails.
  • Staff: Clear thresholds help you decide when to intervene and how many manual reviews to expect.

Verification Modes​

Binary Mode (Pass/Fail)​

Simple pass/fail flow. Best when you want a clear yes or no decision.

  • Threshold: Set a single confidence score (common starting point: 60)
  • Outcome:
    • Score ≥ Threshold: Pass ✅ (Guest continues self check-in)
    • Score < Threshold: Fail ❌ (Guest is directed to the Front Desk)

Three-State Mode (Pass/Review/Fail)​

Advanced flow that creates a manual review step for borderline cases.

  • Upper Threshold: Score required for automatic pass (common starting point: 60)
  • Lower Threshold: Score below which is automatic fail (common starting point: 30)
  • Review Range: Scores between Lower and Upper Thresholds trigger a manual review
  • Email Alerts: Enable notifications to staff when a review is required

Workflow:

  1. Pass: Guest proceeds automatically
  2. Review: Guest pauses or continues (based on policy), staff verify ID manually
  3. Fail: Guest is directed to the Front Desk

Configuration Guide​

  1. Select Mode: Choose between Binary or Three-State
  2. Adjust Thresholds:
    • Suggested Upper: 60-70 (high confidence)
    • Suggested Lower: 30-40 (filters obvious mismatches)
  3. Email Alerts (Three-State only):
    • Toggle Enable Email Alerts
    • Add recipient email addresses for your Front Desk or Security team

Practical Examples​

ScoreBinary (60)Three-State (30/60)
75✅ Pass✅ Pass
50❌ Fail⚠️ Manual Review
20❌ Fail❌ Fail

Best Practices​

  • Lighting: Place kiosks in well-lit areas to improve match quality.
  • Calibration: Start with the suggested thresholds and adjust based on false rejects or extra manual reviews.
  • Staff Training: Train staff on how to handle "Manual Review" and "Fail" cases quickly and consistently.