In 2021, retailers worldwide lost $94.5 billion due to shrinkage, a metric that primarily encompasses losses from internal and external theft and fraud. As shrink rates continue to rise, leading merchants are turning to technology—specifically Exception Based Reporting (EBR) paired with AI security camera systems—to pinpoint loss faster and protect profit.
What is exception based reporting and why it matters
ExceptionBased Reporting is a data-analysis process that flags outliers—transactions or events that fall outside expected patterns. In retail, these outliers often include high-value refunds, repeated voids, coupon abuse, or an unusual number of gift-card sales. Instead of combing through every receipt, loss-prevention teams use EBR software to surface only the anomalies that warrant investigation, saving hours of manual work and focusing attention where it counts. When EBR is combined with AI camera footage and point-of-sale (POS) data, stores can verify incidents in seconds and act before losses escalate.
Key features and benefits of EBR in retail
POS system integration and automated anomaly detection
EBR tools connect directly to modern POS systems to monitor for suspicious activity such as no-sale drawer openings, excessive returns, or price overrides. When an exception is detected, an integrated AI camera platform immediately pulls the matching video clip, giving investigators visual context without hunting through hours of footage.
Advanced data analytics and multi-source exception reporting
Best-in-class solutions merge POS data with video, supply-chain feeds, sensor logs, and more. Consolidating multiple sources provides a single dashboard for loss prevention while automated, customizable reports ensure the right stakeholders receive timely insights.
Real-time alerts and rapid response
AI-powered analytics scan live feeds and transaction streams, sending real-time alerts to mobile or desktop devices. Teams can intervene immediately—whether that means speaking to a cashier about a suspicious refund or dispatching security to a restricted area.
Seamless use of existing hardware and software
Look for platforms that work with your current cameras, POS terminals, and IT infrastructure. Leveraging what you already own shortens deployment time and avoids unnecessary capital expense. Spot.ai customers, for instance, are typically live in under a week.
Automated case management and evidence organization
Integrated case-management tools automatically bundle video, receipts, and notes into a single digital file. This speeds up investigations, simplifies collaboration with law-enforcement or HR, and preserves a clear audit trail.
Spot AI customer story: EBR + AI in action
A national sporting-goods chain, All Star Elite, paired its existing POS data with Spot AI’s video intelligence platform. Within one quarter, cash shrink dropped from 6 percent to 1 percent, and average investigation time fell from two hours to ten minutes.
“When we figure out the correct placement of our Kobe jersey within the store, that typically increases sales by 5 percent to 15 percent because we're able to pull traffic into other areas and get ideas on other products that pair with it.”
— Andrew Gonzalez, Corporate Director of Loss Prevention and Safety
Considerations and limitations
Before rolling out EBR and AI camera systems, evaluate how easily the software will integrate with legacy POS or networking equipment.Plan for staff training to avoid resistance, establish clear alert thresholds to prevent notification overload, and confirm compliance with local regulations governing video surveillance and data use. A phased pilot at one or two locations often uncovers workflow adjustments before full deployment.
Measuring success and ROI
Track shrinkage rates, inventory accuracy, exception audit times, and case resolution speed to quantify impact. Many retailers see double-digit shrink reduction and faster stock reconciliation within the first six months. Dashboards that update in real time help managers spot trends and adjust procedures quickly.
Selecting the right EBR and AI camera solution
Prioritize real-time analytics, accurate object and event recognition, flexible data integrations, scalable storage, user-friendly dashboards, and responsive vendor support. Fast implementation—ideally in under a week—means value is delivered quickly and disruption is minimal.
Staff training and change management
Successful adoption depends on engaged employees. Combine hands-on workshops with scenario-based learning focused on common exceptions. Provide ongoing support, update protocols as new threats emerge, and celebrate quick wins to reinforce the program’s value.
Ready to see how Exception Based Reporting and AI camera systems can reduce loss in your retail business?
Discover how Spot.ai delivers real-time insights and seamless POS integration—going live in under a week. To learn more, book a demo with our experts today.
Frequently asked questions
What is exception based reporting and how does it work in retail?
Exception Based Reporting automatically scans transaction and operational data to flag outliers such as suspicious refunds or voids. Retailers investigate only the anomalies, saving time and focusing on the highest-risk events.
How quickly can an EBR and AI camera system be deployed?
With cloud-based architecture and compatibility with existing hardware, many retailers are live in less than a week, including configuration, testing, and user training.
What types of exceptions can these systems detect?
Common examples include no-sale drawer opens, excessive discounts, repeated gift-card sales, entry into restricted areas, and abnormal inventory movements.
How can I measure the ROI of an exception based reporting solution?
Key indicators include reduction in shrink percentage, faster case closure, recovered merchandise value, and improved inventory accuracy. Comparing pre- and post-implementation metrics provides a clear ROI picture.
Are there any challenges to be aware of when implementing EBR and AI solutions?
Possible hurdles include integrating with older POS systems, managing alert volume, ensuring staff buy-in, and adhering to local surveillance guidelines. A pilot program and comprehensive training help mitigate these issues.
About the author: Mike Polodna is Head of Customer Success at Spot.ai, where he helps retailers implement video intelligence and exception-based reporting systems that deliver fast, measurable results.
