Card Fraud Crackdown May Shrink Interchange

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Credit card fraud costs banks billions of dollars each year, and interchange income is one of the areas most affected. Interchange income is often seen as a source of additional revenue for credit card companies, which in turn makes up some of the money lost to fraud. The way interchange income works means that when purchases are made with a card, merchant services providers collect a fee from their customers and then pay interchange costs to acquiring banks. Credit card fraud severely impacts interchange income due to the large amount of time and resources required for replacements, refunds, and boosting security measures in order to prevent further cases of fraud.

Not only are credit unions facing reduced interchange revenue but may also see unhappy customers who are susceptible to their E-commerce transactions being declined, through no fault of their own. This may be an unintended consequence of the escalating battle between merchant acquiring banks and online card fraudsters.

Merchant acquirers are making big changes to fight a recent surge in card fraud, but those changes could cost credit unions a lot of money. According to Monica Eaton-Cardone, co-founder and COO of dispute mitigation and risk management firm Chargebacks911, a spike in card-not-present fraud in recent months has prompted acquiring banks to put more and more online retailers on their unapproved lists. The result is a mushrooming number of declined transactions, which could threaten interchange income for credit union card issuers.

The trigger was the Oct. 1 EMV liability shift, which transferred the cost of card fraud from EMV card issuers to parties in the authorization chain that don’t support EMV cards. EMV cards generally just mitigate fraud perpetrated at physical point-of-sale locations, however, which is why criminals are quickly pivoting to card-not-present fraud typically perpetrated in online purchases.

Today, 55% of all card fraud is perpetrated online. In 2014, it was 42%, according to a recent LexisNexis study of 959 risk and fraud decision-makers and influencers. It’s also up to seven times harder for merchants to detect fraudulent transactions that aren’t done in person, according to the LexisNexis study. Given all that, online retailers can look increasingly risky, which is fueling demand for third-party providers that use algorithms to flag potentially fraudulent transactions.

While the increased online fraud occurrences drive more anti-fraud solutions, the inflexible nature of current algorithmic software methods may be more harmful to overall merchant sales.

“What’s needed is actually more intelligence and a better method of actually scoring a merchant,” Eaton-Cardone said. “That’s a huge issue currently that we see – there’s no standardization on how to score a merchant to identify that they’ve reached this risk. For credit unions, that may mean dealing with members who blame them for declined transactions or even switch to other cards they believe “work.”

There are growing opportunities in the anti-online (and any) fraud efforts for third-party software firms to leverage advancements in artificial intelligence and data analytics technology. These are machines, as we have seen from IBM’s Watson, that go beyond basic programmed algorithms, and actually try to understand, reason, and learn, just as we humans do. Merchant acquirers could then be able to crunch huge amounts of data, more successfully recognizing fraud patterns, and making sure that legitimate card-not-present transactions are not declined.


Overview by Raymond Pucci, Associate Director, Research Service at Mercator Advisory Group

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