Coresight AI "Sweethearting" detection
Information Certainty: Documented
Deployment Purpose: Commercial Surveillance
| Summary |
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| About a month ago, Israel-based Corsight AI began offering its global clients access to a new service aimed at rooting out what the retail industry calls “sweethearting,”—instances of store employees giving people they know discounts or free items. |
Products and Institutions:
| Product Deployed | Corsight Fortify |
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| Institutions ⠉ | Corsight AI |
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| Search software |
Status and Events:
| Status | Ongoing |
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Description[ ]
A brand new way of being surveilled could be coming to a store near you—a facial recognition system designed to detect when retail workers have anomalous interactions with customers.
About a month ago, Israel-based Corsight AI began offering its global clients access to a new service aimed at rooting out what the retail industry calls “sweethearting,”—instances of store employees giving people they know discounts or free items.
Traditional facial recognition systems, which have proliferated in the retail industry thanks to companies like Corsight, flag people entering stores who are on designated blacklists of shoplifters. The new sweethearting detection system takes the monitoring a step further by tracking how each customer interacts with different employees over long periods of time.
Shai Toren, Corsight’s CEO, told Gizmodo that the system analyzes how close customers stand to different employees and whether returning customers consistently go to the same employee when they visit a store. Anomalies trigger alerts to store security staff, who decide how to proceed.
“If you go into a shop and you pick up a few groceries, usually you would pick any of the cashiers that is around and you go scan your goods,” he said. “When someone is planning a sweethearting theft, they will always go to the same cashier, which is most of the time a relative of theirs, and this is an anomaly in the behavior compared to the other customers. Our system is able to identify this anomaly and alert on that.”1