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Countering the growing level of counterfeit returns

Return fraud is a major issue for retailers and it is proving increasingly problematic for luxury goods retailers as there is a growing trend of fake products being returned instead of original items.

A major UK department store is looking to counter the problem of return fraud by hooking up with US-based Entrupy that has developed its Fingerprinting solution to protect the retail supply chain from the introduction of luxury good counterfeits. The retailer, which could not be disclosed at this time, has deployed the solution.

Before the items are sold at a store or prior to shipping an eCommerce order, the solution captures a single microscopic image of each product and then assigns a unique ID to it. This is the ‘fingerprint’ of the real item, which then can be compared when the item is returned to verify its authenticity.

The solution, which consists of a magnifying lens on the back of an Apple device and an app, captures the item’s fingerprint at 260-times the magnification of the human eye.

Vidyuth Srinivasan, CEO and co-founder of Entrupy said: “While return fraud is a huge industry issue that is rarely talked about, a lot of retailers are realising the scale of the problem and are looking for solutions. Fingerprinting protects the supply chain, scales very well and it also does not physically affect the product.”

One advantage of the solution is that it delivers instantaneous and extremely accurate results, and can be applied to multiple product categories – from shoes and make-up to handbags and jewelery.

Entrupy has another solution that authenticates luxury products on demand and is already used globally by a large number of retailers and resale sites. A magnified photograph is taken of the item, which is then verified by Entrupy’s AI algorithms. These algorithms have been trained using millions of images from over 100,000 unique items. From there, the Entrupy app, which has a 99% accuracy rate, instantly indicates whether the item is authentic or not.

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