Minimize Fraud With 'Payment Intelligence'

Tyson Nargassans for Credit Union Magazine
July 27, 2009 | COMMENTS

According to a recent Gartner survey of 5,000 adults, about 7.5% of Americans lost money as a result of financial data breaches in 2008. The survey reports 7% of respondents had their debit card data used and 6% had a new account opened under their names.

In addition, while 6% of those surveyed said they changed financial institutions last year due to security concerns, that number increased to 28% after they became victims of fraud.

With fraud clearly a key issue for credit unions, how can you identify common points of compromise in fraud cases and use that data to mitigate that risk and retain members?

While neural networks provide some level of detail into potential fraudulent transactions, it can take hours, even days, to go through the mounds of paper-based reports—and that often doesn't happen.

And when it does, it may be too late to minimize the impact and save those members who could have switched to another institution due to the time and money they lost and inconvenience they went through when affected by fraud.

So what's the answer? Payment intelligence.

Payment intelligence, which gives credit unions an understanding of members' purchasing patterns, compliments and enhances a processor's neural network by enabling organizations to better manage the risk and impact of a data breach and use that knowledge to take measures against possible future fraud.

Following are three ways credit unions can use payment intelligence for fraud prevention and mitigation, specifically regarding debit cards.

1. Look for debit card transactions that fly under the radar of rules set up in the neural network. For example, with the prevalence of skimming and duplicate cards being produced, it's possible for multiple transactions to take place in a short time in close proximity for an amount of money that doesn't exceed the daily defined limits.

This could be something like three to four transactions, each for a couple hundred dollars, at ATMs that don't have cameras. These wouldn't trigger alerts in the neural network, but a credit union could stand to lose a sizable amount of money—and possibly members.

With a solution that delivers payment intelligence, a credit union can establish additional transaction sets or pattern limits and be alerted to this type of activity. If the activity is seen, the institution can take proactive measures and contact the potentially affected members to alert them to the suspect activity on their cards.

For those who were affected, the credit union then can block the cards and issue new ones, thereby minimizing the impact on those members.

2. Determine if someone is attempting to capture embedded fraud deterrent codes. With a payment intelligence tool, a credit union can see when it's being attacked by someone who's trying to match codes to a card member, as it will receive a large number of CVC or CVV 1, 2, or 3 denials.

The credit union also may see a large amount of over-the-limit denials or bad personal identification number attempts. With this knowledge, the institution again can take proactive steps to minimize the effect and potential expense of this activity.

3. Leverage payment intelligence data in the case of a data compromise. The knee-jerk reaction to receiving an alert from a card company that member data may have been compromised (e.g., as in the case of Heartland Payment Systems) is to block and reissue all potentially affected cards.

While most institutions will do some analysis to determine which cards already have been cancelled or which accounts have been closed or statused, often that's as far as the analysis goes.

Payment intelligence can take it a step further by enabling a credit union to determine which of those suspect cards/cardholders are top revenue producers for the institution. With that knowledge, the credit union can contact those members to offer to block and replace those cards (versus a widespread block and reissue initiative).

The credit union also can identify those cards/cardholders that haven't produced transactions in the past six months, for example. With those members, a credit union doesn't need to invest the time and money focusing on them now, but can set up additional rules within the neural network and payment intelligence solution to identify suspicious activity on those cards. If any is seen, then the institution immediately can take the appropriate next steps.

Payment intelligence enables credit unions not only to be more efficient with staff time and resources but also with financial resources. With the knowledge and insight a payment intelligence solution delivers, credit unions can employ smarter strategies to mitigate the effects of fraud, and take the appropriate proactive measures to retain member relationships.

Tyson Nargassans is founder and president/CEO of Saylent Technologies, Franklin, Mass. Contact him at 508-570-2161. Reprinted with permission from CreditUnionMagazine.com