Diebold Nixdorf Sets Out to Combat Shrink in Retail with New AI-powered Offering

With millions of checkouts in use by major retailers globally, the company’s newest AI-assisted solutions address the top causes of retailer shrink–all without replacing current infrastructure

Diebold Nixdorf, the provider of retail solutions powering transactions and experiences for more than 150 retailers around the world, today began the rollout of its new AI-based checkout solutions, as first seen at the NRF Big Show this month.

Designed to prevent the most common sources of loss at self-service and traditional POS checkouts, the new Smart Vision technology-powered offering will complement Diebold Nixdorf’s already-live AI-based solutions, which reduce friction during fresh produce scanning and age verification for restricted sales. Bringing these technologies together on a single platform will result in one of the most holistic anti-shrink solutions on the market – with great ability to scale. Diebold Nixdorf can deploy its new AI-powered solutions for retailers, without disruption, through its existing in-store integrations.

Retailers have long recognized the exponential potential that self-service technology offers in terms of customer convenience, optimized floor space and employees’ ability to better engage shoppers. However, managing and mitigating the associated risk of shrink at the self-service checkout has long been a challenge. Poor shopper and employee experiences are also factors that retailers must consider when the self-checkout process is disrupted by the need for human intervention, stock inaccuracies and other points of friction. All of this can detract from the convenience of using self-check outs.

Diebold Nixdorf’s new AI-powered solution, “Vynamic® Smart Vision I Shrink Reduction” is powered by SeeChange’s AI and machine learning cloud platform, and is aimed at satisfying retailers’ need to easily implement and deploy new technologies across multiple store locations and geographies.

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Matt Redwood, vice president, Retail Technology Solutions at Diebold Nixdorf said: “Retailers are committed to innovating, but they want to avoid duplication of efforts and costly implementations. Any new innovation deployed inside stores not only needs to be seamless but must also enhance the customer experience. We designed our new AI-powered offerings based on insights we’ve gained deploying millions of POS and thousands of self-checkouts across the major retailers we work with. We’ve left no stone unturned when it comes to enhancing customer and employee experiences, as well as retailers’ need to scale easily and improve efficiency.”

Effective immediately, Diebold Nixdorf’s new solutions are equipped to reduce the most relevant sources of revenue loss and friction at self-checkout—at scale:

  • Reduce loss across high priority shrink scenarios at checkout. The new AI-based offering will combat common causes of loss, including theft where shoppers deliberately do not scan an item, mistakes where an item is unintentionally not scanned, and situations where shoppers scan only one item of several, use false barcodes or switch them, and pay for some items but leave with more.
  • Autonomously verify age to assist with age-restricted sales. The need to verify the age of a shopper for certain types of purchase is a legal requirement in all countries and can account for up to 22% of interventions by a shop employee. By using a consumer facing camera and requiring the shopper’s consent to use the application, an algorithm estimates the consumer’s age in real time, without storing any consumer information in the system. This enables consumers to privately prove their age in less than 10 seconds, compared to an industry average of three minutes when employee verification is required.
  • Identify and distinguish between fresh produce items. Diebold Nixdorf’s AI-equipped self-checkouts additionally speed up the process of purchasing produce that is priced by weight or quantity, such as fruit, vegetables or other loose non-barcoded items. Through a combination of camera-enabled computer vision and extensively trained algorithms, the system identifies the produce and quantity so that shoppers no longer have to, and retailers’ margins don’t suffer due to misidentified items.

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