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COmpany
COmpany
Guide to facial recognition for retail crime prevention
Retail violence is rising and facial recognition is increasingly part of the response. But getting it wrong carries real consequences. This guide gives leaders and their teams the framework to evaluate it responsibly, build the internal case, and choose the right partner.
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year-on-year increase in retail crime involving weapons
average loss reduction at stores with ASR
of verified ASR matches recorded no incident at that visit
WHAT'S INSIDE
The guide to responsible facial recognition for retail crime prevention
A practical guide to facial recognition for retail crime prevention, covering the technology, the risks, and what responsible use requires in practice.
- The violence and repeat offending trends driving facial recognition adoption across markets
- How facial recognition works, what affects accuracy in a real retail environment, and what separates responsible application from riskier alternatives
- How Auror Subject Recognition is built around responsible use, with the intelligence, workflows, and human oversight that make it effective in practice
- A practical path from initial evaluation to confident implementation
For privacy, legal, and IT teams
A practical framework for assessing whether a deployment is responsible and defensible.
For LP/AP and operations leaders
The market context, the technology factors, and risk management to lead this decision with confidence.
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Who it's for
This guide is designed to travel. Download once, then share it with the people who need to weigh in.
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