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Why time and attendance systems need to verify who is clocking in?
Card swipes, PINs, or QR codes confirm a check-in—not the identity behind it. This creates opportunities for time fraud.
- 75%+companies report financial losses from buddy punching
- $1,560average employer loss per employee, per year, from buddy punching
- 4.5 hrslost to time theft per employee, per week (avg.)
Source: American Payroll Association — Biometrics and Beyond: Innovating Against Buddy Punching Losses
Even small amounts of unverified time can create significant payroll losses and affect workforce management. Use the calculator to estimate the impact.
A 100-employee workforce with a $40 average wage and 15 minutes of unverified time per day could face up to $260,000 in annual payroll leakage.
Calculate the cost of attendance fraud
EXAMPLE
Based on 260 working days/year — actual leakage varies by shift complexity and existing controls.
Annual payroll leakage
$26,000
Accurate attendance starts with biometrics
Face recognition and liveness detection confirm that each check-in belongs to the registered employee.
- Time and attendance softwareAdd face-based employee verification to existing clock-in and clock-out workflows.
- Workforce management systemsImprove attendance accuracy for workforce planning and operations.
- Field workforce & remote teamsVerify employees across distributed locations — even offline.
A practical biometric attendance workflow
See how face identification and liveness detection work in a time clock system.
Explore 3DiVi Face SDK — trusted face recognition for attendance
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Face recognition
Verify employees during check-in with 1:1 authentication or 1:N identification. -
Liveness detection
Prevent spoofing using photos, video replays, 2D/3D masks, and AI-generated faces. -
Fast integration
Integrate biometric features within weeks, not months. -
Flexible deployment
Run on devices, on-premises, in the cloud, or hybrid. -
Scalable performance
Support growing employee databases with high-performance face matching. -
Cross-platform
Run across Windows, Linux, Android, and iOS, with support for Python, C++, C#, Java, Kotlin, Swift, Flutter, Go, and Node.js.
CLIENT PROOF
Challenge: A major organic producer needed reliable employee attendance tracking across remote plantation sites with a seasonal workforce and limited connectivity.
Result: Employees could be identified at check-in without relying on manual timekeeping, helping reduce proxy check-ins across multiple locations.
ORGANIC MANUFACTURER AND SUPPLIER
Solution: 3DiVi Face SDK was integrated into a tablet-based .NET application, adding face recognition and liveness detection to the existing attendance workflow.
Attendance tracking across remote macadamia plantations
Featured resources
Key questions on face recognition in time and attendance systems
A time and attendance system can use face detection and recognition to identify employees, along with liveness and deepfake detection to help prevent spoofing.
3DiVi Face SDK provides the core biometric capabilities to add face recognition to time and attendance software, including face detection, liveness and deepfake detection, and biometric matching. It can be integrated into an existing system without developing face recognition technology from scratch.
Face recognition identifies the employee at check-in, making it much harder for one person to clock in on behalf of another.
Yes. 3DiVi Face SDK can be integrated into attendance terminals, kiosks, tablets, smartphones, and other compatible devices with a camera.
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