Fraudsters online are masters of mimicry. They understand which signals and shopping behaviors raise red flags for merchants and work to avoid them by employing strategies that imitate those of legitimate consumers. For example, Riskified observes that fraudsters often combine “safe” physical goods with risky items in a shopping cart, mixing, for example, lower value physical-product purchases (which merchants usually treat as lower risk) with high-value digital purchases or gift cards (which merchants usually treat as higher risk).

While they may have no interest in the physical goods, this strategy boosts the chances of the order being approved. Malicious actors also prepare stolen accounts by gradually creating realistic activity, such as making small purchases, processing returns, and browsing, so the accounts appear established and reliable before launching their attack.

And, of course, they exploit seasonality by increasing activity during busy periods, such as Travel Tuesday, or when elevated legitimate volume makes anomalous behavior harder to detect.

But during the biggest sales season of the year? There’s a holiday twist. During the end-of-year peak sales season, good customers flip the script and exhibit behaviors that would usually raise red flags but are legitimate. This makes it more important than ever for merchants to have identity-based fraud intelligence to determine fraud hustles from welcomed shopping.

A lot of normal holiday behavior looks downright risky

Not only are fraudsters playing their usual obfuscation games during the make-or-break season for merchants, but the typical holiday consumer may also start looking riskier. Bigger baskets, faster shipping, and atypical addresses and logins become commonplace. If merchants use hard-and-fast rules with manual review rather than adaptive and identity-based fraud detection, they risk mistaking good purchases for those of bad actors, which can cause lasting harm to relationships and revenue.

Here are a few examples:

Naughty or nice, machine learning sees clearly

Whether it’s fraudsters adopting tactics to appear like good customers or vice versa,  the solution for merchants is the same: automated decisioning, machine learning, and identity-aware intelligence based on cross-network data. Riskified empowers merchants to accurately differentiate between good customers and bad actors beyond just the holidays, preventing fraud and preserving a positive customer experience.

Read the report to learn more about how Riskified automation can help you thrive in our holiday guide for merchants. You’ll also discover:

  • How to instantly recognize 85% of new customers so you can calibrate checkout for facilitation or friction
  • How AI assistants are changing consumer behavior and merchant risk
  • Category-specific trends, including electronics, travel, fast fashion, and gift cards
  • Regional fraud risks and anomalies from EMEA and LATAM