When Will They Strike? Understanding Fraud in Online Shopping
Retail transactions during peak shopping periods, especially online and mobile sales, continue to increase each year — with the 2018 holiday shopping season serving as a prime example. The season saw record sales, with Black Friday far exceeding expectations and Cyber Monday becoming the largest online shopping day in U.S. history.
E-commerce and m-commerce retailers and shoppers often assume these peak sales periods increase the possibility of fraud, but the data is in and that’s actually not true. In last year's third quarter, Sift analyzed 165 billion transactions and other fraud-identifying data to see how fraud stacked up in 2017.
What we found is that — contrary to popular belief — the most fraud doesn’t happen during the Thanksgiving and Christmas holidays. In 2017, May 9 actually saw much higher fraud rates than any other day of the year. What’s more, July 14 was the highest fraud day of 2017 for online retailers. The common assumption is that because peak sale periods like Black Friday and Cyber Monday see heightened shopper traffic, fraudsters strike harder on those days. This leads retailers to put more into fraud detection efforts during specific peak shopping seasons, often neglecting the days not associated with these.
In reality, fraud ratios drop during peak sales periods due to the amount of legitimate transactions being filled. While the overall number of fraudulent transactions may increase during peak shopping events, it’s overshadowed by the massive influx of legitimate transactions. The importance here for retailers is ensuring legitimate orders are filled, while fraudulent ones are caught — no matter the time of year.
Ways Retailers Can Ensure Legitimate Orders Are Fulfilled Year-Round
Getting ahead of fraud risks and empowering legitimate customers to shop without friction, especially during peak shopping events and seasons, will maximize your bottom line and help you to retain customers. To do this effectively, retailers need to do the following:
1. Armor Up With Information
Analysis of trends from previous years gives retailers information and details around potential launches that may cause changes in customer behavior. Consistent testing of anti-fraud systems and teams will also help retailers ensure the organization is ready to handle the increased volume (and increased fraud potential) of peak shopping periods.
2. Proper Staffing and Resources
Before a peak sales period, figure out if temporary help is needed, and give yourself time to properly train contractors so they’re equipped to deal with the fraud rush. Cross-training customer support team members is also a good way to prep for peak sale increases. Planning is key, and the earlier you begin the process the better. Ideally any new team will be locked and loaded at least a few weeks in advance so you have time to review performance before the rush begins.
3. Empathy is Key
Keeping morale up within retail organizations is always crucial, but especially during peak shopping seasons. Letting a team know their work is appreciated helps motivate them when building the customer experience. Empathy also applies to customers, new and returning. Consumers are often stressed during shopping frenzies, so a little empathy goes a long way when communicating with them to secure sales and drive loyalty.
Assuming how and when fraudsters will act around peak shopping times shapes how retailers protect against fraud and also the willingness of consumers to shop. When assumptions are wrong, it impacts the bottom line — e.g., cancellation of legitimate orders. The good news is that new technologies enable fraud detection and prevention faster and more accurately than ever, meaning better, frictionless experiences for legitimate customers and the potential for sustainable growth. This will be increasingly important for retailers as we look at fraud peaks and trends in 2019.
Kevin Lee is a trust and safety architect at Sift who helps customers implement strategies that cross-functionally align risk and revenue programs. He has lead various risk, chargeback, spam/scams, and trust and safety organizations at Facebook, Square and Google.