Lords report calls for easier means to report retail crime
According to a report by the House of Lords Justice and Home Affairs Committee, shoplifting is being seriously underreported, leading to steep shrinkage and raising safety issues for the retail staff and genuine shoppers. The report paints a grim picture on the crime situation, emphasizing the need for police to take immediate action and respond to complaints (see news).
Why is retail crime underreported?
Underreporting of retail crime occurs mainly due to the time-consuming and laborious process of collecting evidence of the event. The store staff needs to sift through hours of CCTV video footage, shortlist the segment that contains the relevant footage, collect a still photograph of the event, fill in the relevant forms, and then send these documents and media to the law enforcement.
Additionally, the process of reporting crime is not consistent and varies across regions. To add to this, of all the events reported, only a few shortlisted events are taken up for follow-up action by the police. All the time consumed in gathering evidence is thus wasted and disincentivizes stores from reporting crime.
Visual AI simplifies the task of reporting retail crime
Visual AI can be a huge timesaver when it comes to collection of evidence of retail crime. Using machine learning algorithms and data analytics, a visual AI solution can detect suspicious behaviour and automatically create a collection of short videos that capture such events.
SAI Group’s Visual AI platform provides – at the press of a button – consolidated video footage which can be submitted to law enforcement, thus saving valuable time and effort spent in sifting through hours and hours of footage. This can greatly enhance the efficiency of theft and concealment detection, and reporting of incidents along with legally admissible footage.
Comprehensive monitoring for the store
SAI Group’s visual AI platform, which can be easily integrated with existing CCTV hardware, provides monitoring of the key areas of the store, including:
- Aisle
- Counter
- Self-Checkout Counter
The platform can also detect suspicious customer behaviour which contribute to retail shrinkage. Here are a few scenarios that SAI Group’s visual AI solution can detect:
| Cause of Loss | Customer Behaviour |
|---|---|
| Incorrect Scans | The customer deliberately weighs lower priced products. |
| Product Switching | The customer uses the barcode of different product to avoid paying the actual price of the product. |
| Product Stacking | The customer places multiple items in a stack and scans the barcode of only the items placed at the top. |
| Missed Scans | The customer fails to scan items from the cart or moves items over the scanner in such a way that they are not scanned. |
| Non-Payment | The customer walks out without finalizing the payment for the items scanned. |
SAI Group provides Visual AI, data analytics, intuitive dashboards, and robust reporting capabilities to three of the top retail companies in the UK. Contact us today, if you are on the lookout for a Visual AI solution that provides almost immediate return on investment.
About SAI
As a leader in computer vision technology, SAI Group delivers cutting-edge, multi-modal AI solutions into retail environments. Using a unique platform approach, its technology uses existing camera systems to target losses, increase store safety, and underpin operational efficiencies.
All solutions are built from the ground up to ensure the highest levels of security and data protection, respecting the privacy expectations of the public and operating to stringent ethical standards while delivering substantial value to our clients. Globally, SAI monitors millions of transactions per day, protecting the revenues from tens of millions of product sales and hundreds of millions of customer interactions. Its models also accurately identify anti-social behaviour, aggression and violence, helping to de-escalate situations with real-time interfaces to security officers and operations centres.
