top of page

C2RO BLOG | Raising the Bar in Retail Safety: Biometric-Free AI Video Analytics for Theft Deterrence

Drawing of a megaphone on a chalkboard saying the word shoplifter.

In recent years, the retail industry has been introducing increasingly frictionless self-payment systems to reduce operational overhead and simplify the customer experience. These technologies put more control in the hands of the consumer and allow retailers to focus more on customer service with a more streamlined cost approach. However, the gains in operational efficiency are being offset by persistent losses due to theft at the self-checkout kiosks. Traditional security measures often fall short of accurately identifying and preventing theft, leading to significant losses for retailers. Biometric -Free AI has emerged as the most powerful method of quantifying the problem and delivering safe deterrence mechanisms to curb the losses and seamlessly restore the full benefits of automated checkout systems.

Explore with us in this blog how Biometric-Free AI Video Analytics has reshaped security practices in retail. By pinpointing behavioral patterns that are leading to system bypass, this groundbreaking technology eliminates the dependence on intrusive biometric measures, marking a significant shift in our approach to safeguarding these environments.

Current Landscape of Theft in Retail Environments

Retailers worldwide face an ongoing battle against theft, with traditional security systems struggling to keep pace with increasingly sophisticated techniques employed by shoplifters. Despite the presence of surveillance cameras, the ability to accurately pinpoint and prevent theft at checkouts has remained a significant challenge. Most theft behavior is extremely subtle and happens in a way that is not obvious to anyone watching the transaction. Having a constant physical presence both onsite and reviewing security footage is both expensive and ineffective in offering proper deterrence because the events are sparse and happen randomly throughout the day, often slipping through the cracks of staff presence or the auditor’s attention span.


Understanding Suspicious Patterns That Lead to Theft

The introduction of Biometric-Free AI Video Analytics marks a paradigm shift in combating theft at self-checkout kiosks. This technology utilizes advanced artificial intelligence algorithms to analyze behavioral patterns without relying on biometric data. By understanding and interpreting gestures, movements, and other behavioral cues, the system can predict potential theft in real time, enabling a proactive approach to deterrence.

The AI system continuously evaluates real-time behavior against the learned baseline. Deviations from the expected patterns are flagged as anomalies. These anomalies may include actions like attempting to bypass scanning items, spending an unusually long time at the checkout, or displaying other atypical behaviors.

Once the system can successfully detect suspicious behavior or anomalies, the retailer can evaluate various forms of soft deterrence. The definition of a seamless and non-intrusive deterrence method is an extremely important part of the process and will be the subject of future elaboration.

Addressing Limitations of Traditional Security Systems

Biometric-free AI Video Analytics provides a solution to the challenges faced by physical retail and augments traditional security systems by addressing the scale and accuracy limitations of security that rely on physical presence and footage review. The technology's ability to analyze complex human behaviors offers a more comprehensive approach, surpassing the capabilities of simple surveillance cameras or outdated security measures. Moreover, the systems offer a data collection capability that produces powerful insights and statistics that can be objectively studied by operations teams and allow for continuous improvements to systems over time.

In conclusion, the breakthrough in tech innovation through Biometric-Free AI Video Analytics presents a revolutionary solution to deterring theft at checkouts and allows self-checkout technology to fully deliver on its promise of increased operational efficiency and improved customer experience. As retailers embrace this cutting-edge solution, they can create a safer and more secure shopping experience while safeguarding their assets and preserving customer trust.

What makes C2RO a recognized pioneer in privacy-aware AI video analytics? C2RO’s organizational, technical, and physical safety measures related to C2RO ENTERA software were carefully audited by the company’s office of the DPO through an in-depth Privacy Impact Assessment (PIA). The results of the PIA were then reviewed by the CNIL, the French national data privacy supervisory authority, as well as by a Canadian law firm which concurred that C2RO ENTERA™ does not present high residual risks for the privacy rights of individuals, making C2RO ENTERA™ the first AI video analytics technology providers to be compliant with both European and Canadian data privacy laws.

C2RO’s solution allows commercial real estate and enterprise customers to leverage their existing surveillance cameras to understand how visitors engage and behave in their physical spaces by analyzing their demographically classified journeys. With better visibility into how visitors navigate your physical spaces, you can identify inefficiencies in your operations and issues in security, allowing you to improve visitors’ experience. Moreover, the newly captured insights in physical spaces can be combined with customers’ digital footprint, allowing for a 360-degree view into visitor behavior to build effective marketing strategies that create a unified visitor experience.

Continue to drive the business goals that are critical for your success with C2RO ENTERA™

Discover ENTERA™: ➡️

Connect with us Today: ➡️


Commenting has been turned off.
bottom of page