Retailers like Target, Walmart and Home Depot have been hit by a spate of organised shoplifting and theft. Businesses have been reducing operating hours, locking up items and threatening to shutter stores completely. New research from the British Retail Consortium (BRC) has revealed that incidents of theft have increased by 26 per cent across 10 of the largest cities in the UK, with some cities seeing a rise of as much as 68 per cent.
Centre for Retail Research, UK, found that shoplifting burnt a hole of US $ 840 million in Britain’s pockets. Over the past year, the industry in the UK spent a whopping US $ 312 million to keep crime out of their doors. ‘Shrink’ — an industry term covering shoplifting, employee theft and organised retail crime — will decline profits this year for US-based Target by US $ 500 million more than 2022.
To address these crimes and to make the retail experience safe for both customers as well as staff, these retailers have taken steps to use advanced technologies like AI and RFID which have come to the fore as solutions that can help in preventing organised shoplifting at each point of the supply chain.
Scale and scope
US-based National Retail Federation (NRF) says organised retail crime (ORC) is the main reason for retail ‘shrink’ — a mismatch between actual inventory and what is on the books, which is increasing by US $ 4 billion year-over-year. In Singapore, about 3,200 shoplifting cases were logged in 2022 – 600 more than in 2021. Hong Kong reported 1,207 cases of shoplifting – a rise of 35 per cent – in the first two months of this year.
Walmart has shut four stores in Chicago, while department stores Macy’s and Target have closed locations due to millions in losses from ‘rampant theft’. San Francisco has seen multiple closures of stores including Nordstrom and Saks OFF 5th.
Target Chief Financial Officer Michael Fiddelke said that shoplifting resulted in over US $ 400 million in losses in the fiscal year. According to industry experts, this is a very sophisticated problem, with local, state, national and transnational organisations, organised not just to steal at the store level, but throughout the entire supply chain which includes on the docks, on trucks, off ships, through containers, on the railways.
Cargo theft is occurring at multiple points in an item’s journey, with the NRF finding that theft ‘en route from distribution centres to stores’ was the top target, at 47.4 per cent; followed by cargo theft at stores, at 42.1 per cent and cargo ‘en route from manufacturers to distribution centres’ at 35.1 per cent.
| New research from the British Retail Consortium (BRC) has revealed that incidents of theft have increased by 26 per cent across 10 of the largest cities in the UK, with some cities seeing a rise of as much as 68 per cent. |
Retail precautions and results
Walgreens CFO said in January that after spending a ‘fair amount’ on private security companies, the results were ‘largely ineffective’. Also, precautions like safety boxes for items and increased presence of security or greater surveillance is not producing the results that these retailers hoped.
The majority of retailers (just under 70 per cent), as of the 2022 NRF data, said they do not have an organised retail crime team in place. This staffing issue contributes to the issue of accurately tracking the theft. Retailers with a dedicated organised retail crime response team were almost twice as likely to report an increase as those without an in-house ORC team, the NRF found.
| Walmart has shut four stores in Chicago, while department stores Macy’s and Target have closed locations due to millions in losses from ‘rampant theft’. San Francisco has seen multiple closures of stores including Nordstrom. |
What more needs to be done – present and future solutions
From license-plate recognition systems and perimeter surveillance to AI-facial recognition and multi-sensor parking lot surveillance towers/units with RFID chips and IoT sensors using blockchain technology, there are many new technologies through which retailers are trying to help curb organised retail theft.
Retailers have begun to use automatic license plate recognition systems (ALPR) technology for a variety of use cases. What ALPR systems do is use video technologies to automatically scan these license plates and record where and when they have been identified. Loss prevention teams put together ‘evidence packs’ of crimes committed by the same person/gang (photos and videos of offenders, products stolen, locations, time of day, etc). As part of this work, ALPR is being used to associate particular vehicles with offenses, individuals and gangs involved, often across multiple locations (the cameras can also produce images of occupants of vehicles as well).
AI Facial Recognition system is another new technology that has become popular in retail stores in order to prevent theft. Combined with high-resolution cameras, these systems monitor customers coming in and out of the stores and track their movements. These technologies allow retailers to monitor their stores and detect unusual behaviour, such as customers lingering near high-ticket items or moving in restricted areas. Macy’s in the US is using facial recognition in stores to address the problem of theft.
Similarly, item tags, such as RFID (radio-frequency identification) tags, can provide retailers with essential data on what was taken, when and via which exit. This data can be analysed to determine if the theft was internal or external, find shoplifting patterns, predict future theft and update the retailer’s inventory view. Lowe’s, an American retailer, has recently implemented a proof-of-concept called Project Unlock, which uses radio frequency identification (RFID) chips, Internet of Things sensors and blockchain technology. The solution is currently being tested in several Lowe’s stores in the United States. Zara is also using chips sewn onto clothes to monitor the movement of items.
| AI Facial Recognition system is another new technology that has become popular in retail stores in order to prevent theft. Combined with high-resolution cameras, these systems monitor customers coming in and out of the stores and track their movements. |
Also, current self-checkout terminals contain several sensors and measures to reduce theft and fraud. These technologies often include a downward-facing camera, an item scanner/front-facing camera and a scale in the bagging area. Self-checkout monitoring systems use machine learning algorithms to analyse transactions and detect fraudulent activity. The system can then block the transaction or alert staff to act.
More recently, AI-driven prescriptive analytics platforms can continuously monitor POS (point-of-sale) and inventory data for anomalies. This data can then be analysed thoroughly, which could indicate theft, fraud and waste, as well as missed revenue opportunities or non-compliance with store policies.
Versions of generative AI, such as AI-powered chatbots, have already demonstrated their ability to find relationships among data. By using natural language processing to communicate in human language, the technology promises to find new applications for tracing theft and fraud.
