Shop Safe – Invest in security tech
When it comes to shop theft, robust tackling has been, in some retail sectors, seen as largely unnecessary due to what is seen as “acceptable shrink,” particularly amongst fast-moving, high-volume retailers in the grocery sector.
Historically, losses were factored into operating margins, and security investment beyond basic CCTV was often deemed non-essential.
But shoplifting is increasing.
The 50,000 retail locations we work with across the UK have seen an increase of over 20% in reported crime through our Alert platform, with some areas showing rises of over 400% in the last 12-months, writes Elliot Blenkhorn, Managing Director of British crime prevention technology provider Shop Safe.
The impact goes far beyond stolen stock. Staff safety is now one of the retail sector’s most urgent concerns. We are hearing consistently from clients that frontline staff are facing rising levels of intimidation and violence – and many are leaving the industry as a result. Retail crime is no longer a “cost of doing business”; it is a workforce issue, a wellbeing issue, and a threat to store operations. If we want stable businesses and vibrant high streets, we must ensure retail workers feel safe, supported and protected.
To address staff security, at the same time as minimising profit loss, retailers are taking a smart, AI-enabled approach which is having a transformative effect on the ease and effectiveness of their retail crime prevention. The focus is shifting from reactive loss prevention, to proactive risk management – identifying threats early and intervening before incidents escalate.
Data is key to offender prosecutions
In the last two years, we have seen an incredible 95% increase in the adoption of our Alert Crime Intelligence Platform. We think this is primarily due to our platforms’ ability to enhance, record and process data – data which leads to arrests, fines and prison sentences for offenders.
Our Alert platform, launched with Hobbycraft in its 100 stores nationwide, has already led to 143 weeks of prison sentences, 60-months’ worth of Criminal Behaviour Orders (CBOs), 12 fines, and the national identification of 16 previously unknown offenders. Custodial sentencing for shoplifting is extremely rare in the UK, making the 143 weeks of prison time achieved highly significant. The results are driven directly by the quality, consistency and evidential strength of data.
Many retailers, especially large brands with dispersed stores, don’t have a clear understanding of the true root of crime across their business, especially in relation to travelling, organised retail crime groups. When it comes to crime evaluation, data quality is a major challenge, due to a reliance on in-store reporting – both in terms of achieving accurate data, and because incidents are often underreported altogether. In some locations, incident reports contain limited detail or no images at all, meaning retailers are often operating without meaningful intelligence.
Without concrete data and useful insight, it is impossible to understand where issues lie, and security systems can’t be rolled out sensibly. AI-tech helps plug this gap. AI-enhancements mean data can be enriched and generated from additional sources. Retailers can build richer incident records, develop detailed offender profiles, identify patterns, and unlock hidden insights that manual reporting would miss.
Machine-learning analytics help identify repeat offenders and high-impact individuals, streamline workflows with intuitive reporting tools, and provide head office with a central, real-time picture of risk across all stores. This type of automation supports retailers to predict, prevent and protect more effectively.
Known offenders identified within 15 seconds
For retailers looking to protect staff from known and violent offenders, facial recognition technology is a game-changer, and the technology is becoming increasingly powerful and advanced.
Facial recognition allows retailers to identify people who have a prior criminal history within seconds of entering their premises. Our customers get notified within 15 seconds of someone entering who is a known offender or shoplifter – their face is securely matched against an authorised database, recorded and shop floor staff are notified in real time.
Past concerns over red tape have been addressed by new legislation and our approach to data storage in this regard is very considered. While we don’t comment on the specifics, retailers are now much more confident in deploying facial recognition as part of a wider security ecosystem. Retailers are taking a flexible approach to its adoption, with some choosing cameras on entry and others opting for body worn cameras.
Our Integrated AI-Powered Facial Matching also allows them to identify repeat offenders across locations – even when information is limited, improving their ability to take preventative action.
Integrating body worn equipment
In October, Tesco announced it was to become the first major UK retailer to roll out body worn cameras, so its delivery drivers ‘feel safer.’ There is no doubt that body worn equipment acts as a deterrent – especially when it comes to avoiding the escalation of a shoplifting incident into intimidation and violence against staff. The presence of a body worn camera alone can de-escalate situations before they become physical.
Aside from a visual deterrent, body worn cameras that are integrated within a wider security solution, provide more ‘eyes’ to spot crime patterns across the shopfloor and identify offenders.
Using body worn cameras and CCTV, our Alert System can process not only facial profiles but also detect theft patterns and object concealment. The platform brings together facial matching, scene analysis, ANPR and offender databases into a single, joined-up security solution. It can track single individuals and shoplifters operating in groups, tying it all together with police-logged criminal profiles and external cameras recording ANPR. It is extremely advanced and provides a powerful, joined up security vision solution for retailers.
This evidence is critical – and AI’s ability to automate and streamline its collection also tackles a universal issue in retail crime: underreporting. Historically, incidents were often not reported because the process was too time-consuming, fragmented and inconsistent across police forces.
Our approach condenses this process into a single, standardised workflow. Instead of multiple stakeholders submitting separate reports, incidents are logged once, triaged automatically and enriched with supporting evidence, bringing together body worn camera footage, CCTV images and facial recognition data.
There is also a broader national movement towards standardising the information required for retail crime reporting, with discussions ongoing around the potential consolidation of police forces and the use of a single online home for submissions. As software providers, it is critical that we support this standardisation, reducing variation between reports and enabling data to be shared seamlessly with police systems.
By combining body worn cameras, AI-driven intelligence and one-touch police reporting, retailers are not only improving conviction rates – they are making it easier for staff to report incidents, feel supported, and stay safe at work.
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