New store formats, checkout models, and customer expectations are rewriting the playbook for loss prevention teams everywhere. Some environments demand frictionless shopping to keep experiences smooth. Others require tighter controls to combat theft. Most global retailers need both— and all face the same challenge: do more with less, in an increasingly complex environment.
Traditional loss prevention tools— manual audits, reactive alarms, and CCTV footage— can’t keep pace. The result? LP teams risk flying blind when they should be in control.
Today, shrink isn’t just about stolen goods — it’s about product availability, profitability, and ultimately, the customer experience.
Peak events can pile up faster than teams can review them. AI Smart Mode assigns each event a relevance score, cutting through thousands of signals to surface the highest-impact cases first and helping teams focus on the incidents that matter most.
Hot items are items that are seen the most by our system leaving the store unpaid. Having up-to-date information on items with the highest loss rate, you are able to quickly adapt your loss prevention strategy to these items. iD Cloud Loss Prevention not only provides insights into your hot items but also into your hot categories.
Store and division overview pages make it easy to find the locations that matter most. Start with the stores or divisions showing the highest losses and use data to focus your efforts where they’ll have the biggest impact.
High Theft Hours helps identify when and where losses occur — by store, day, and time. With these insights, you can optimize staff and guard planning, and improve in-store training to raise awareness during peak theft periods.
Through autonomous monitoring of voided transactions, Sweethearting Events detect potential fraud early, allowing retailers to intervene before losses escalate.
Peak Events indicate potential theft when several items exit the store at once, a common sign of ORC activity. The platform detects and flags these events automatically — even without confirmed payment data.
Validate events, with for example CCTV footage or staff interviews, and keep track of all your theft events.
Out of Hours automatically flags events where items exit the store outside of regular operating hours. Such activity may indicate internal theft or the unauthorized resale of high-profile products.
The security hard tag has been a helpful ally to apparel and fashion retailers in deterring theft. The mere fact that a hard, plastic tag was attached to an item,......
Read more64% of retailers say that ORC has become more of a priority for their organization in the last 5 years.
NRF Organized Retail Crime Survey, 2022
Modern loss prevention demands more than alarms and assumptions. It requires rich, contextual understanding across all retail operations. When stock moves, it leaves a digital footprint. Each footprint tells a story, whether it comes from POS transactions, ERP events, inventory counts, or EAS triggers.
iD Cloud combines these footprints into a unified intelligence layer that translates fragmented data into clear, prioritized actions. It connects HQ strategy with store-floor execution, enabling LP teams to move faster, smarter, and with greater confidence.
Traditional alarms lack context. iD Cloud combines multiple data sources, including items leaving the store, POS transactions, and stock counts, to detect suspicious activity in real time.
iD Cloud identifies loss patterns and risk hotspots with precision. By combining data from POS systems, Workforce Management tools, and Inventory Management software, retailers can track:
iD Cloud Loss Prevention is built for central loss prevention teams, providing a smarter, more efficient way to detect, investigate, and prevent losses. It automatically generates precise, time-stamped incident reports (e.g., “12:34 – products X and Y stolen”) instead of vague summaries, improving data quality and reducing investigation time. The system learns from validations to surface the most relevant events, not just the noisiest, enabling faster, smarter decisions. With context-rich alerts and workflows, loss prevention teams can resolve cases in minutes — no data analysts required.
Machine learning algorithms detect data patterns before shrink escalates, enabling early identification of:
With item-level visibility, retailers are no longer in the dark once stolen goods leave the store. Every tagged item carries a unique digital identity, showing when it was last seen, where it exited, and whether it was sold.
This level of detail accelerates recovery in several key ways:
No loss, no matter where, should go unnoticed.
Oscar van den Broek, Managing Director of Nedap Retail
Embedded machine learning continuously analyzes data, refining its predictive models to:
