Self-Checkout Loss Prevention Solution

Self-checkout loss prevention is retail loss prevention technology that detects loss at self-checkout lanes in real time and prompts a correction before the transaction completes. Scandit Self-Checkout Loss Prevention uses vision AI to detect the patterns behind most self-checkout loss, missed scans, items left in the basket, and walkaways, and recovers or deters more than 75% of it. It analyzes the transaction, not the person, so no shopper is identified.

A camera at the lane, using software powered by vision AI, watches the scan session and correlates what it sees with the scanner and point-of-sale data. If an item leaves the scan zone, bagging area, or basket without a valid scan, the shopper gets a soft on-screen nudge to rescan, which resolves most cases with no associate involved. If a shopper leaves mid-transaction, a short clip escalates to an associate who makes the final decision, with every step configurable to the retailer's own policy.

It detects the loss patterns behind 97% of self-checkout loss: missed scans, items left in the basket or trolley, and walkaways, along with barcode switches. The system reads item movement and flags a discrepancy when what the scanner and POS expect does not match what happens at the lane (ECR Self-Checkout Loss Report, 2026).

Retailers can recover or deter more than 75% of self-checkout losses with Scandit Self-Checkout Loss Prevention, through soft on-screen nudges, associate alerts, and per-store loss visibility.* Most flagged cases never reach an associate: shoppers self-correct in 80 to 97% of cases once nudged (ECR, 2026).

*Based on Scandit calculations.

No. It analyzes the transaction, not the person: it reads item movement correlated with scanner and POS data, and never uses facial recognition, builds or stores a biometric template, or re-identifies a shopper from one visit to the next. Live video is processed at the lane to support retailers' GDPR obligations, backed by Scandit's ISO 27001:2022 certification, and because it identifies no one it avoids by design the practices the EU AI Act prohibits.

Where a retailer already has cameras at the lane, the self-checkout's built-in camera or a standard security camera above it, the existing hardware can usually be used, alongside a per-station processing unit. Retailers deploying for the first time may need new cameras and units, but there is no purpose-built AI camera, no proprietary hardware to buy into, and no dedicated in-store server.

Both remove friction at the self-checkout lane, but they are separate products with different architectures that share no data. Age Verified Self-Checkout uses a one-time, on-device facial age estimate on the shopper's own phone to clear age-restricted items, with nothing stored. Self-Checkout Loss Prevention processes no facial or biometric data at all; it only analyzes item movement to detect loss.