How does computer vision detect loss at self-checkout?

Cameras monitor each transaction in real time. The system analyses what is happening at the terminal, tracking items as they are handled and identifying when what is present does not match what has been scanned. When a potential loss event is detected, the system prompts the shopper to review their items before the transaction closes.

Does computer vision use facial recognition?

No. Retail computer vision for loss prevention is behavioural, not identity-based. It detects patterns, not shoppers, checking for whether an item was scanned, how products are being handled, and whether a transaction is complete. No biometric data is collected.

Is computer vision GDPR compliant?

Compliance depends on how the system is designed. Systems built on a privacy-by-design architecture are aligned with both GDPR and the EU AI Act.

Does computer vision work with existing camera systems, or is new hardware required?

In most cases, existing infrastructure can be used without replacement. Modern computer vision systems are hardware agnostic and integrate with most POS systems. Depending on the deployment, GPU or CPU upgrades may be required, and these are typically scoped per store.

Will computer vision create friction for shoppers?

Computer vision is designed not to create shopper friction. When a potential loss event is detected, the system prompts the shopper to review their items via a screen message (a soft nudge that allows self-correction without staff involvement.)

What is the ROI of computer vision in retail?

Independent research by Forrester into Everseen's platform found retailers achieved 374% ROI over three years. On a per-store basis, the average uplift is $88,000 annually. ROI will vary by retailer, estate size, and the use cases deployed.

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