Retail theft is becoming an increasingly pressing issue in the United States, with annual losses estimated to exceed $100 billion. While shoplifting and employee theft remain significant concerns, a rising threat is “sweethearting,” a form of insider fraud where employees provide unauthorized discounts or free items to friends or family. This type of theft often goes unnoticed as employees manipulate systems, such as bypassing item scans, issuing false refunds, or misusing employee discounts to facilitate these transactions.
To address this challenge, Corsight AI has introduced a facial recognition-based sweethearting module aimed at identifying and preventing these fraudulent activities. According to Gal Biton, Corsight’s global VP of sales, the facial intelligence platform scrutinizes interactions between employees and customers to detect unusual patterns. The system flags suspicious contacts for further investigation by security teams, helping to reveal instances of sweethearting where customers, in collusion with cashiers, leave with unpaid merchandise.
This sweethearting module is part of a comprehensive AI-driven retail security suite that also features tools for tracking individuals on watchlists, detecting unauthorized access to restricted areas, and monitoring loitering or behaviors often associated with theft. With concerns about retail crime on the rise not only in the U.S. but globally, retailers are increasingly exploring such technological solutions.
Research from SIA indicates that senior retail executives view facial recognition technology as a vital weapon against theft. A recent survey conducted by the UK-based firm Opinion Matters among 300 senior retail leaders in the U.S. and the UK revealed that at least 15 of the top 50 grocery stores in the U.S. have already implemented facial recognition technology.
In addition to Corsight, another notable player in the market is Facewatch, a cloud-based facial recognition system that compares real-time images against a pre-existing database to identify potential matches linked to previous theft or antisocial behavior. When a match occurs, the system promptly alerts store staff, enabling them to take swift action.
Globally, the adoption of facial recognition technology in retail is gaining traction. A pilot program in New Zealand grocery stores has shown promising results in detecting and reducing theft, suggesting a viable model for broader implementation. Meanwhile, in the U.K., lawmakers are actively discussing the potential for facial recognition as a retail tool, given the rising theft rates. However, the expansion of this technology is not without controversy. In New York City, for example, there is a proposed bill that seeks to limit the use of facial recognition in grocery stores, highlighting growing privacy and surveillance concerns among the public.
In response, grocery store owners in New York City are voicing their opposition to this proposed legislation. Additionally, the city council is considering a measure requiring businesses to inform customers and obtain written consent before using biometric recognition technologies, with hefty fines for noncompliance. As the conversation around retail theft and security continues, it’s clear that technology, particularly facial recognition, is playing an increasingly critical role in the fight against retail crime.