20% of Shrinkage Due to Self-Checkout
Work with SAI Group to Reduce Loss
Self-Checkout (SCO) is witnessing greater adoption, with millions of items being scanned across stores of retail chains. While this has helped retail chains showcase a futuristic tech-savvy store with fewer personnel, loss prevention officers are staring at rising self-checkout fraud, highlighting the risks associated with unmanned counters without sufficient monitoring.
Challenges with Self-Checkout
SCO was expected to reduce the burden of monitoring and enable friction-free shopping for customers. However, with retail shrinkage hitting a record high, amounting to billions of GBP, and one-fifth of losses being attributed to self-checkout, it is important that loss prevention officers take cognizance of the different types of frauds that can occur at the SCO counters.
Here is a quick summary of what could go wrong at a SCO counter:
| Cause of Loss | Customer Behaviour |
|---|---|
| Incorrect Scans | The customer deliberately weighs lower priced products instead of items that are priced higher. |
| Item or Product Switching | The customer scans a lower value item and places another item in the bag. |
| Missed Scans | The customer fails to scan items from the cart or moves items over the scanner in such a way that they are not scanned. |
| Non-Payment | The customer walks out without finalizing the payment for the items scanned. |
Current Solutions and Challenges
Retail stores have tried out announcements of the scanned items’ names such as “Potatoes” as a deterrent to customers walking away with more expensive items by scanning bar codes of cheaper items. However, this places an additional burden on the store personnel who now need to intervene in a timely manner at the SCO counters.
Another method that has been tried out is to carry out analytics of the customer activity and predict that an erroneous scan has occurred. This involves piecing together the information from the scanner, the item being scanned, the volume or weight of the item in question, and sending an alert to the appropriate store staff so that they can make an intervention. This can prove to be time-consuming, and the staff will feel edgy to intervene as they are not yet sure if it is a case of malintent on part of the customer.
The Future is Here
Of the many technical approaches available such as analytics, a Visual AI solution using the existing infrastructure appears to be the apt choice. To reduce chances of SCO Frauds, SAI Group's Visual AI solution offers the following automated, timely interventions:
- Send alerts to the store staff over their handsets or the terminal when:
- Items are mis-scanned
- Some items in the cart are not scanned.
- Items are stacked and only the top one is scanned.
- Display a warning message on the monitor located above the SCO stating that some issue has occurred, and that the activity is being monitored.
- Display a warning message on the SCO screen stating that a suspicious action has been recorded and give the option for the customer to take corrective action using SAI Nudge.
SAI Group's Visual AI solution boosts customer satisfaction through self-correction, cuts wait times, and eases staff workloads. It also effectively reduces shrinkage at self-checkout counters.
SAI Group offers various solutions to deal with SCO frauds. Our streamlined AI is cost effective and scalable – and trusted by the best retailers.
Contact us to learn more about our products and services for retail loss prevention.
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About SAI
As a leader in computer vision technology, SAI Group delivers cutting-edge, multi-modal AI solutions into retail environments. Using a unique platform approach, its technology uses existing camera systems to target losses, increase store safety, and underpin operational efficiencies.
All solutions are built from the ground up to ensure the highest levels of security and data protection, respecting the privacy expectations of the public and operating to stringent ethical standards while delivering substantial value to our clients. Globally, SAI monitors millions of transactions per day, protecting the revenues from tens of millions of product sales and hundreds of millions of customer interactions. Its models also accurately identify anti-social behaviour, aggression and violence, helping to de-escalate situations with real-time interfaces to security officers and operations centres.