Webinar recap: Introducing Auror Subject Recognition

Retail crime has become more violent, more organized, and more dangerous for frontline teams. Globally, 1 in every 10 retail incidents now involves violence, and repeat offenders are up to 6X more likely to cause serious safety events. Store teams face the reality that someone who walked out with merchandise yesterday might return tomorrow with a weapon.

Traditional approaches to preventing these incidents have left retailers with an impossible choice: accept the rising threat to their teams or implement technology that raises serious privacy concerns. Auror Subject Recognition changes that equation by combining leading facial recognition technology with verified Retail Crime Intelligence for responsible recognition.

Why recognition technology matters now

Violence in retail stores has shifted from occasional incidents to a tactical part of organized retail crime (ORC). Phil Thomson, Co-founder and CEO of Auror, explained this change during the ASR webinar:

"People are happy to steal in front of others. People are happy to walk out of a store knowing that they're being watched by a security team, caught on camera, and with the public at large looking and watching them as well. And as part of that trend, this violent piece has really come to the fore."

The numbers reflect this reality. In the US, 1 in 8 retail events involve threatening behavior. In Australia, threatening behavior in retail has increased by 32% in the last 12 months alone. Store closures often follow these trends in violence, removing access to essential goods from communities.

Recognition technology has existed for years, but previous implementations created as many problems as they solved. Issues with accuracy, bias, transparency, and scope creep made many retailers hesitant to deploy facial recognition despite the growing safety crisis.

Intel that protects people and their privacy

Auror Subject Recognition addresses these concerns through a fundamentally different approach. Rather than categorizing people based on demographics or tracking shoppers through stores, the system focuses exclusively on identifying known high-risk persons of interest before they offend again.

Nick McDonnell, Senior Director of Global Public Policy, Trust & Safety at Auror, described the distinction:

"This is not about profiling based on demographics. It's about identification for safety and prevention based on verified intel about past serious behavior."

The system operates through several key principles:

1. Privacy-first design: No biometric data stored within the retailer’s information in Auror. If there is no match, both the detection image and temporary biometric template is discarded immediately. The technology doesn't capture or process sensitive characteristics like race, religion, or political affiliation.
2. Human verification: Every detection requires human review before action. Store teams receive alerts with context about past incidents, allowing them to make informed decisions about how to respond appropriately. A human is always in the loop on key decisions.‍
3. Purpose-built controls: Technical safeguards prevent misuse from the start. The system can only be used for crime prevention — never for tracking shoppers, marketing purposes, or unauthorized enrollment.

Explore the safeguards in place for Auror Subject Recognition here.

How the system works

Auror Subject Recognition integrates directly into the existing Auror platform that retailers already rely on for Retail Crime Intelligence. Store teams continue their normal workflows without learning new systems or processes.

When a known, high-risk person of interest enters a store, the system generates an alert that includes critical intel: what happened in previous incidents, whether violence was involved, and what outcomes resulted. This context helps teams respond safely, or choose not to engage if the person has a history of weapons or extreme violence.

Thomson explained the advantage:

"How do you turn that information into person of interest management? Everything is automated in that sense. You're not having to go and put this information into a different system at every single store manually. Everything is automated, bringing up that information to an investigator or admin person to review and confirm."

The system works with existing camera infrastructure in most cases, making implementation straightforward. Independent testing confirms exceptional accuracy even in challenging real-world conditions — achieving a 1 in 100,000 false positive rate even with poor lighting, masks, and off-angle views.

Key takeaways

The webinar highlighted several critical points about responsible recognition technology:

1. Violence has become tactical: Repeat offenders increasingly use violence as a deliberate strategy to commit retail crime, not just as a reaction when confronted.‍
2. Small groups drive disproportionate harm: 10% of offenders cause more than 60% of retail crime, and these same individuals are 6X more likely to cause serious safety events.‍
3. Technology has improved dramatically: Advances in both camera quality and recognition algorithms have made accurate, reliable facial recognition possible in real retail environments.‍
4. Privacy and safety can coexist: Purpose-built safeguards, human verification, and transparent policies enable effective prevention without surveillance or demographic profiling.‍
5. Integration matters: Standalone point solutions create silos and operational friction. Embedded capabilities within existing workflows drive adoption and results.

Building safer stores responsibly

Auror's mission is to reduce violent retail crime by 50% in the next five years. Subject Recognition represents a critical tool in achieving that goal, giving retailers a way to protect their teams from known high-risk individuals without compromising privacy or creating surveillance systems.

As McDonnell noted:

"We want to have good relationships with regulators, not just for this product, but for a whole bunch of things that we do. When you explain how we built the system to deal with the decisions they've made in the past around systems being as safe, transparent, and trusted as possible, there is relief when we talk through all the safeguards we've put in place."

Watch the webinar recording clips above to hear detailed explanations of how Auror Subject Recognition works, see demonstrations of the platform's privacy controls, and learn how retailers are using this technology to create safer stores today.

Visit Auror Subject Recognition to explore the technology in depth, or contact us to learn more about how Auror can help protect your stores from violent repeat people of interest while also protecting privacy.