While the first documented shoplifting incident took place in 16th century London, retail crime remains a very current issue to retailers worldwide. And it is on the rise.

In Australia and New Zealand, retail theft offences have been steadily increasing and are up 47.5% year-on-year, having already amounted to over $2 billion.

Opportunistic crimes are being driven by the rising inflation and cost of living pressures, but today’s shop owners worry about more than the occasional Shoplift.Organised retail crime is now targeting high-value items to resell them online for a profit. Retail workers shortage and poorly-monitored, self-service checkout systems all but facilitate such crimes.

So, how can retailers beat these challenges to safeguard the business against loss?

Recently, on the Axis Retail Leadership forum, customers and industry leaders joined Axis to discuss how AI and technology can be used to prevent organised retail crime and enhance operational efficiencies for stores.

From network surveillance for visual incident detection and theft prevention, to data analytics for in-store insights, there’s a range of solutions that help identify suspicious activity swiftly, facilitate rapid response, and proactively prevent future incidents.

The impact of AI and Machine Learning in retail operations

With rising concerns over staff shortages and pressing demand for enhanced operation efficiency and productivity, the retail industry is directing greater investments towards automation and AI-driven augmentation technologies. This has led to widespread adoption of self-checkouts and self-service options in stores.

However, while this rise of in-store automation alleviates workloads, it also brings new challenges when it comes to loss prevention, safety, and security.

AI-driven surveillance cameras and sensors provide retailers with invaluable real-time insights, enabling them to spot risks, uncover intricate patterns often overlooked by human eyes, and expedite data analysis. With access to this data, loss prevention teams can promptly detect anomalies or suspicious actions, reposing swiftly and effectively to threats before they escalate.

And this type of advanced technology offers more than just real-time detection of suspicious behaviour. By analysing historical data and identifying recurring incidents, such as repeated thefts, AI can uncover patterns and identify potential perpetrators. This capability empowers retailers not only to prevent future incidents but also to hold accountable those responsible for security breaches. The growing adoption of machine learning in retail security underscores how AI is revolutionising loss prevention strategies.

Integrating AI into the surveillance infrastructure with privacy best practices in mind enables businesses to make better informed decisions and empower their security protocols.

Integrated solutions for enhanced retail security

Besides AI and machine learning, integrated network solutions remain fundamental to retail security and loss prevention initiatives, encompassing cameras, audio, sensors, access control, video management systems (VMS), and analytics. These comprehensive solutions enable the visualisation of each point-of-sale (POS) transaction, allowing for the visual scrutiny of abnormal voids, refunds, or exchanges to mitigate shrinkage.

Furthermore, the video footage of product returns aids in combating the escalating problem of return fraud, which nearly 4 in 10 Australian online shoppers (39%) admit to having either engaged in themselves or know of someone who has in the past 12 months. These behaviours, encompassing outright fraud, return policy abuse, and other unfavourable return behaviours, highlight the pressing need for robust security measures in the retail sector.

Integrated solutions offer numerous opportunities to identify and prevent suspicious behaviour in high-risk zones:

  • Self-checkouts: Video analytics can be used to detect a non-scanned product and alert the shopper and the store management if needed.
  • Cart pushout: Video analytics and audio alerts can be used to identify customers leaving the store with a full cart without paying and direct them back to the till.
  • Transactions occurring without customer presence: Installing a sensor on the cash register to detect when the drawer is open. Connected with a camera, this can be used to confirm whether the transaction is happening with customer presence, and notify management if necessary. This can be useful in instances of employee theft, that are not as common as customer theft, but tend to incur higher costs to the business.
  • Monitor high value goods: As mentioned, organised retail crime is targeting high-valued items. When a door or lid connects wirelessly to a camera, opening or lifting it triggers sensors to zoom in and capture the moment. Similarly, when a staff member swipes a card over a reader to unlock the cabinet, this action logs the time and identification. Both scenarios provide insight into who accessed the cabinet and when, while also capturing visible evidence simultaneously.
  • Loitering: By integrating audio features and analytics, retailers enhance the ability to respond promptly to suspicious activity. For instance, cameras can identify prolonged shopper presence in an area and trigger an alert to on-site staff or remote operators for assistance.
  • Deliveries: The risk of shrinkage extends beyond the shop floor, particularly during deliveries. To mitigate this, authorised deliveries can be verified using intercoms, QR codes, or licence plate recognition. Remote access control can be implemented, and cameras—either wearable or fixed—can visually confirm the accuracy of goods being loaded and unloaded. Analytics can also help identify vehicles on-site, with edge-based analytics triggering alerts to relevant personnel, such as security or law enforcement, upon detecting a suspicious vehicle.

Integrated network solutions in retail bolster business operations by identifying potential risks and generating alerts that can be responded to based on urgency. These capabilities contribute to improving profitability through strengthened loss prevention measures.

Securing the future of retail through advanced loss prevention measures

Retail crime is on the rise, impacting the industry significantly. However, technological advancements, particularly in AI and machine learning, offer a beacon of hope for retailers seeking to enhance their security and protect their bottom line.

By leveraging integrated network solutions encompassing surveillance cameras, audio, sensors, access control, and analytics, retailers can proactively detect and deter suspicious activities across various touch points within their operations.

These solutions not only enable real-time monitoring and rapid response to incidents but also empower retailers with valuable insights for future decision-making. As the retail sector continues to embrace AI-driven technologies, it is poised for a transformative journey towards greater efficiency, profitability, and resilience against emerging security threats.

Rodney Guinto is retail segment manager at Axis Communications.