Scandit Debuts Real-Time Vision AI Self-Checkout Solution to Reduce Loss During Self-Checkout

Scandit announced Self-Checkout Loss Prevention, a real-time vision AI solution that helps retailers detect loss patterns as they happen. The solution empowers shoppers to self-correct, without store associate intervention in the majority of cases, to keep the checkout flow uninterrupted.

“Self-checkout fundamentally changed retail, but it also changed the loss equation,” says Christian Floerkemeier, Scandit CTO and co-founder. “Retailers shouldn’t have to choose between a fast checkout experience and strong loss prevention. Self-Checkout Loss Prevention gives them a software-first way to detect issues in real time with the process configurable to a retailer’s own policy. In addition to recovering losses, it also enables retailers to optimize labor usage more productively.”

Key takeaways:

·        With Self-Checkout Loss Prevention, a soft on-screen nudge to shoppers, or attendant notification if escalated, corrects any flagged items before a transaction is completed, resulting in the recovery or deterrence of more than 75% of losses attributed to self-checkout. This includes known loss patterns such as missed scans, intentionally skipped items, left in trolley and abandoned transactions.

·        Self-Checkout Loss Prevention deploys as a per-station architecture that eliminates the need for dedicated servers and complex installation while unlocking a scalable deployment from small store formats to large hypermarkets.

·        The hardware-agnostic solution works with existing camera infrastructure - whether built-in, off-the-shelf, or standard security cameras above the self-checkout station - eliminating the need for purpose-built AI hardware to maintain a low total cost of ownership.

·        The solution processes video on the station and is designed to support retailers in meeting their GDPR obligations.