How does Clarity's AI technology detect counterfeit returns?

Clarity's AI scans returned products, learning what genuine items should look like and then identifying anomalies such as different organic materials or missing parts.

What is the impact of counterfeit returns on retailers?

Fraudulent returns, including counterfeits, are costing retailers tens of millions of dollars annually due to the rise in return rates and dishonest practices.

Which company is using Clarity's technology first?

ReturnPro, a returns-management company, will be the first to use Clarity's machines to screen returns in three of its U.S. facilities.

Home / Business and Economy / AI Spots Fake Returns in Seconds

AI Spots Fake Returns in Seconds

5 Feb

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Summary

New technology uses AI to detect counterfeit merchandise within returned items.
The system can identify fakes by scanning for different organic materials.
Retailers experienced a rise in fraudulent returns, costing millions.

Clarity, a startup, has emerged from stealth mode with technology aimed at helping retailers combat counterfeit merchandise within returned items. This innovative system utilizes artificial intelligence to scan returned goods, identifying potential fakes in roughly three seconds. Retailers have seen a substantial increase in return rates since the pandemic, with an estimated 9% of returned goods being fraudulent, leading to significant financial losses.

The AI-powered machine functions similarly to an airport security screener. By scanning an example of a genuine product, the AI learns its expected appearance. It can then detect anomalies, such as different organic materials or missing components like power cords, flagging items as potential counterfeits. This allows retailers to avoid reselling fake merchandise and to trace problematic returns back to customers.

ReturnPro, a returns-management company and a strategic investor in Clarity, will implement the technology in three of its U.S. facilities. Clarity's leadership includes former Walmart executives, and its technology was developed by a Carnegie Mellon University professor. The company's solution is intended to supplement the work of warehouse employees by providing a faster and more accurate method for counterfeit detection.