Data on the price ranges that online fraudsters target most are effective in helping retailers be more aware of fraud tendencies. However, any price point can be a target to some criminals, and it’s important to leverage this data to build a more effective approach to fraud reduction without sacrificing revenue or customer experience. Here are some ways to go about it.
As CNP fraud continues to increase, we often see reports about the price ranges fraudsters are targeting most heavily in different industries. For example, the $100 to $500 range was the sweet spot for many fraudsters looking to steal furniture, appliances, and power tools online, according to the October 2017 PYMNTS Global Fraud Index. A 2017 Juniper Research white paper put 2015 average fraud order values around $1900 for airline tickets, about $1700 for automotive purchases, and around $600 for pharmacy orders. Figures like these can help businesses protect themselves from fraud, but only if they’re used correctly. Simply adding a rule to an automated fraud-screening program is not enough, and it can even lead to more losses.
What does fraud price-range data tell us?
Reports and updates on commonly targeted price ranges are snapshots in time that show what CNP fraud looks like at that particular moment. They serve as cues to look more closely at your own fraud rates in those ranges and to review your fraud protection practices. Over time, these snapshots can show how fraud is trending in a particular price range within a specific vertical. That information can have an impact on the overall risk profile and processing costs for merchants in those verticals.
However, any price point can be a target to some criminals. Because stolen payment data is so cheap now, some fraudsters use it to buy takeout meals and transportation instead of reserving that data for the theft of expensive goods for resale. And some verticals always seem to deal with more fraud attempts than others, such as apparel, jewelry, electronics, beauty, travel, and health and wellness.