Using AI Self-Checkout to Boost Risk Management and Customer Satisfaction

Are your self-checkout systems contributing more to shrinkage than savings? While self-checkout kiosks offer many benefits such as faster checkout times, increased autonomy, and improved convenience, they also present significant challenges for retailers. Rising incidents of theft, fraud, and operational losses are increasingly linked to self-checkout systems. 

With the global self-service kiosk market projected to reach USD 43.65 billion by 2028, the vulnerabilities that savvy customers exploit continue to grow. So, how can retailers effectively mitigate these losses?

Understanding Self-Checkout Operations

To comprehend the complexities of this issue, it’s essential to examine how self-checkout kiosks typically operate. These systems combine various technologies, including sensors, cameras, and barcode scanners. When a customer uses a self-checkout (SCO) system, they generally follow a sequential process:

1. Scanning: Customers scan the barcode of each item, which the system registers.
2. Weight Verification: Many systems incorporate scales that verify the weight of scanned items against expected weights, adding a layer of security.
3. Payment Processing: After scanning all items, customers proceed to payment via card or mobile options.

While this system offers convenience, it also opens the door to numerous opportunities for dishonest behavior. Tactics such as the “banana trick,” where customers scan a lower-priced item like a banana instead of a higher-value product, or the “switcheroo,” where a customer swaps an expensive item with a less costly one, can lead to significant losses. There are also instances where customers may inadvertently leave items unscanned, resulting in incomplete payments and complicating loss prevention for retailers.

READ ALSO: Don’t Let Inventory Issues Hold You Back. Here’s how you can take Control!

Using Video AI to Improve Security Against Self-Checkout Fraud

Video AI is addressing self-checkout vulnerabilities by optimizing traditional methods with advanced visual recognition and real-time behavior tracking. Here’s how it’s reshaping loss prevention while improving the customer experience:

Multi-Dimensional Product Detection

Video AI enhances product recognition by utilizing advanced visual recognition technologies, such as machine learning and facial recognition, to identify items based on various characteristics rather than solely relying on barcodes. This approach enables the system to accurately recognize products even when barcodes are missing, damaged, or obscured, helping to prevent theft and fraud.

Data-Driven Insights for Store Layout and Design

By analyzing video data, retailers can gain insights into customer flow and checkout patterns. Self-checkout kiosks located in blind spots or areas with less direct supervision are often the most commonly misused, as customers may feel emboldened to engage in suspicious behaviors when they believe they are not being watched. This information can guide store layout and design changes, optimizing visibility and supervision at self-checkout areas.

READ ALSO: Discover How Video AI Can Skyrocket Your Holiday Retail Sales!

Seamless Integration with POS Systems

Video AI integrates with existing Point of Sale (POS) systems to cross-reference scanned items with transaction data in real time. This integration allows for comprehensive audits of self-checkout transactions, simplifying the investigation of discrepancies and enhancing accountability for any suspicious activities.

Customer Behavior Monitoring

How effectively are you monitoring customer behaviors at self-checkout? Video AI oversees the entire checkout process, detecting suspicious actions like skipping the scanner or bagging unscanned items. For example, if a customer scans a low-value item while concealing a more expensive one, the system recognizes this pattern through body movement and item placement. By catching these behaviors in real time, Video AI enables quick intervention before losses occur.

Adapting to New Tactics

As AI learns from customer interactions, it continuously enhances its detection capabilities. This adaptability ensures that the system evolves alongside emerging fraud tactics, providing a future-proof solution for retailers.

Combat Self-Checkout Shrinkage with Dragonfruit AI 

At Dragonfruit, we pride ourselves on delivering a robust Self-Checkout Theft & Loss Prevention solution while leveraging your existing infrastructure. Our offering includes:

• Seamless Integration and Affordability: We work with your current camera infrastructure, meaning no need for expensive new hardware or complex installations. 
• Accurate Product Recognition: While standard systems may struggle with damaged barcodes or product swapping, the Dragonfruit Self-Checkout Theft & Loss Prevention solution utilizes advanced machine learning to visually recognize products based on features such as shape, texture, and packaging. This ensures accurate price look-up images and improved loss prevention.
• Holistic Transaction Analysis: Recognizing that the self-checkout process is a continuous event, our solution analyzes the entire checkout process in real-time for suspicious activities. This ensures swift detection of patterns and anomalies, such as skipped scans or hidden items.
• Low Friction, High Accuracy: Dragonfruit minimizes customer interruptions by focusing on high-risk events, reducing false positives, and ensuring that only genuine cases of fraud trigger alerts.

Don’t let self-checkout loss hinder your business growth. Discover how Dragonfruit AI can transform your approach to loss prevention and elevate your customer experience. Schedule a demo today!

Request a Meeting

‍

Disclosure: The products promoted on this page are offered by Dragonfruit AI, a provider of app-based video AI business solutions. Read more about Dragonfruit AI here.