Is Your CNP Fraud-Detection System Confused by Consumer Behavior Now? That Could Damage Your Business

The COVID-19 pandemic has transformed how consumers behave. These changes could be causing a spike in good orders mistaken for fraud, creating irreparable damage for businesses.

The COVID-19 pandemic has abruptly changed how people shop. With stay-at-home orders only now starting to lift in some areas, a lot of commerce has moved online, and what people buy has changed, too. These changes in consumer behavior are understandable to humans. To your e-commerce fraud-detection system, however, the way good consumers act now may no longer make sense. That could be causing a spike in good orders mistaken for fraud. 

False positives aren't a new problem in e-commerce, but an increase in rejected orders is the last thing merchants need right now. Each false decline represents a missed sale and the possibility of a lost customer at a time when the future of many retailers seems uncertain. Recalibrating fraud programs for the new normal is critical for generating revenue now and keeping customers over the long term. 

Why your fraud rules may be rejecting good orders now

Fraud-screening programs are built to compare customer information and behavior to known consumer data, shopping histories, biometrics and what's considered normal activity for legitimate consumers. The problem facing online sellers now is that nearly every customer behavior that raised a fraud flag in the prepandemic era is something good customers are doing now. 

Let's look at typical red-flag behaviors and how they align with today's shopping patterns. You may spot some areas where your fraud controls need adjustment. 

  • Buying items in bulk, especially large quantities of in-demand items, raises the possibility of a fraudster ordering items for resale. But as grocery stores and big-box chains sold out of essential items like hand sanitizer, bleach and gloves earlier this year, many consumers placed bulk orders for those items online.
  • Customers ordering items outside their usual purchase patterns may indicate that a criminal has taken over the account to buy items to resell. For example, fraud programs may flag an order from a customer who's never purchased fitness equipment before if they buy a pricey fitness bike. But that's what many people are doing as gyms remain closed.
  • Making multiple purchases from the same or different merchants on the same day can be a sign that someone's using a stolen credit card to go on a spree. But as shoppers try to find everything on their quarantine shopping lists, more of them are checking sites several times a day and buying items as soon as they find them.
  • Making high-ticket value purchases from new merchants is another fraud-shopping-spree flag. It's also normal behavior now. For example, as much of the U.S. went into stay-at-home mode earlier this year, grocery and big-box stores quickly sold out of toilet paper as well as cleaning supplies and masks. That pushed some consumers to order online in bulk from office supply stores, home health suppliers and commercial janitorial supply houses they'd never shopped with before.
  • Ordering from or shipping to new areas can indicate a purchase by someone using a stolen credit card. But with some people quarantining away from home, by choice or by happenstance, it can also indicate a good customer. Likewise, orders placed from an unfamiliar device could indicate fraud – or someone using a quarantine housemate's desktop or phone to order supplies. 

Clearly, a number of fraud indicators that worked well before the pandemic now overlap with new normal behaviors of good customers. Why do some fraud programs treat them the same? 

The core of the problem isn't flagged behaviors. It's what the fraud program does with the information. Systems that automatically reject flagged orders are naturally going to kick out more good orders when more good orders are getting flagged. That costs e-commerce merchants the value of the declined good orders. It also costs them customers. In fact, 19% of cardholders will never shop with a merchant after an order rejection, while 24% will shop less often with the merchant.

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