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Illustration by Security Management

Can Technology Address Warranty Fraud? 

Late last week, the U.S. Attorney’s Office for the Eastern District of Pennsylvania announced it had charged Jerel Andre Williams with warranty fraud related to Cisco hardware components. Williams allegedly obtained serial numbers for parts and claimed the parts were defective in ways he knew could not be solved through troubleshooting. The charges cover 157 warranty claims over two years, with each one dealing with parts with a retail value of between $3,693 and $34,500. Williams is also charged with filing false tax returns, underreporting gross receipts by more than $600,000 over two years.

The scheme involved fake email addresses and shipping the parts to several addresses in six different states in an effort to fool fraud control systems. The defective parts were supposed to be shipped back to Cisco; however, the charges allege that Williams did not return any parts.

Cisco has been the target of major warranty fraud schemes before. Almost a decade ago, Iheanyi Frank Chinasa was sentenced to a seven-year prison term when he and an accomplice defrauded Cisco of $27 million worth of parts by returning counterfeit equipment as defective.

According to a study by IBM of electronics manufacturers, 8.1 percent of rejected warranty claims were rejected as fraudulent. In addition, 3.6 percent of approved claims are later discovered to be fraudulent. According to artificial intelligence and machine learning solutions provider Tavant, blockchain technology could eventually be a powerful tool in combating fraudulent warranty claims:

“Once the complete lifecycle of a part is available through a trusted public ledger, it would be possible to see the exact time and place of manufacture, note when the part transited through the warehouses of the distributor or supplier, check when it showed up in the seller’s inventory, and find out when and to whom it was finally sold. This detailed traceability would make it very easy to detect counterfeits, which would fail to show the expected transition history through the supply chain of authorized manufacturers, distributors, and sellers.”