Fraud for online holiday sales spikes by 31%

Number of e-commerce transactions grows by 16%

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Fraud attempts on digital retail sales jumped 31% from Thanksgiving to Dec. 31 over the previous year, according to a survey of purchasing data from ACI Worldwide.

The fraud increase was based on hundreds of millions of online transactions with major merchants globally. Also, the number of e-commerce transactions grew by 16% for the same period, ACI said.

Some of the fraud attempts came from the use of credit card numbers purchased in underground chat channels, ACI said.

“Given the consistent and alarming uptick in fraudulent activity on key dates, merchants must be proactive in their efforts to identify weak spots and define short and long-term strategies for improved security and enhanced customer experience,” said Markus Rinderer, senior vice president of platform solutions at ACI.

ACI provides electronic payments technology for more than 5,000 organizations globally. One of its products, ReD Shield, was used to collect the data in the survey. ReD Shield, a fraud detection and prevention software product, was used to process 7% of all Black Friday online spending and 13% of Cyber Monday’s spending.

The data showed that the highest fraud attempt rates were on Christmas Eve and on days when shipments were cut off. The key shopping dates by volume (number of transactions) were Cyber Monday, which showed 15% growth, and Black Friday, which showed 19% growth.

The average sales ticket declined by 7% during the 2016 holiday period. The average was $228 in 2016, down from $243 in 2015.

In 2016, one of every 97 transactions was a fraudulent attempt, compared with 1 out of 109 transactions in 2015.

ACI defines a fraud attempt as a transaction confirmed by a merchant as fraudulent; a transaction that matched a record in an ACI database for a credit card number that was sold online in an underground chat channel; or as reported as fraud by a bank or other issuer. ACI also includes as fraud attempts those data patterns that match a recently confirmed fraud behavior.

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