UK Startup Uses AI to Help Retailers Reduce Shrinkage at Point of Sale
Retailers are constantly battling to protect their profits — up to 50 percent of which are lost to theft.
Now, they have a new weapon in their armory.
ThirdEye Labs, a London-based company and member of Inception, NVIDIA’s startup incubator, is combining off-the-shelf CCTV cameras with state-of-the-art AI algorithms to detect anomalous activities in stores.
Caught AI Handed
Every year, U.S. retailers lose up to $32.25 billion due to theft.
In addition to those pocketing items straight from the shelves, it’s estimated that one percent of all customers who visit self-service checkouts steal. Sometimes it’s accidental — an item doesn’t scan through properly or the wrong type of pastry is selected from the bakery menu.
But some people follow schemes such as “the banana trick” (steaks scanned as potatoes) or “the switcheroo” (scanning the barcodes of cheaper items, instead of a pricier purchase).
To date, retailers’ attempts at deterrence have had little effect. Hiring more security personnel is expensive and creates unpleasant shopping experiences. While security alarms are evaded and self-service counters continue to be deceived.
ThirdEye Labs’ AI algorithms help security staff work more effectively and efficiently. Trained on NVIDIA GPUs, the company’s deep learning networks can detect specific indicators of fraudulent behavior from CCTV footage and then alert staff, who can take appropriate action on the spot.
“We chose to train our algorithms on NVIDIA GPUs as they are fast, reliable and effective,” said Raz Ghafoor, CEO and co-founder at ThirdEye Labs. “Without the power of these GPUs, our development time would have doubled.”
ThirdEye Labs’ AI software can be used with existing security infrastructure — no additional hardware or software is needed. None of the video footage used is recorded or stored anywhere and the system doesn’t perform any facial recognition, meaning the system is GDPR compliant.
At stores where ThirdEye Labs’ system has been introduced at self-service checkouts, the AI technology analyzes every scan to detect non-scans, non-payments, substitute scanning and fraudulent refunds. Over the course of a month, two stores flagged a few dozen suspect transactions, up from basically zero, by implementing ThirdEye Labs’ point-of-sale system.
In the aisles, too, fraudulent behavior hasn’t gone unnoticed. ThirdEye Labs’ “In-Aisle Theft Detector” sends security guards push notifications every time someone picks up high-risk items, like champagne bottles or fresh meat. They can then decide whether or not to take action, helping them work more efficiently and effectively.
The service has saved stores tens of thousands of dollars in losses by helping security guards have their eyes on the right behavior, at the right time.
The Future of Convenient Shopping
ThirdEye Labs plans to expand its technology to improve customer shopping experiences.
Its “Queue Detector” will predict when lots of customers are about to get in checkout lines. By alerting staff, tills can be manned before the rush.
Its “Stock-out Detector” will help stores monitor their shelves and identify when stock is low. Empty shelves cost retailers an estimated three percent of their total revenue each year, so optimizing stock replenishment has big benefits for sellers as well as those looking to purchase.
The post UK Startup Uses AI to Help Retailers Reduce Shrinkage at Point of Sale appeared first on The Official NVIDIA Blog.
![[D] Siraj Apologizes and Promises Refunds within 30 days](https://b.thumbs.redditmedia.com/UkSa8Nu83Y_CO3cAi8q0RsSyzNpcUVKdTa7t_W8HmWg.jpg "[D] Siraj Apologizes and Promises Refunds within 30 days")
![[D] Understanding proof of MaxEnt theorem](https://a.thumbs.redditmedia.com/WkxdF2_DI5UQHaNb_K2bxtyIcDbf1lwSQDAbaAeka68.jpg "[D] Understanding proof of MaxEnt theorem")
![[P] I've made User Behavior Prediction for everyone, called Behaiv](https://b.thumbs.redditmedia.com/M1sRRbDlIFKGfQzgbjWPswKCITYJBbvFdUkV286tlDs.jpg "[P] I've made User Behavior Prediction for everyone, called Behaiv")
