[Ebook] Digital Trust & Safety for QSRs: Why legacy rules can’t keep up

It’s not every day that the average person associates quick-service restaurants with cutting-edge technology—after all, french fries and milkshakes are quintessentially basic. But today’s QSRs offer far more than traditional American fast food fare, serving up globe-spanning cuisines and delivering a world of dining options to consumers that are only possible with the help of emerging technologies. 

From in-house ordering kiosks to mobile-driven delivery, leading QSRs are rapidly expanding their toolsets to provide customers with the fastest, easiest routes to a full stomach. But all of this growth, innovation, and adoption of digital-first platforms has a dark underbelly—and that’s where fraudsters are quick to take their seats at the table. 

With great speed comes great responsibility 

The QSR market is one that’s already worth billions of dollars and getting more valuable by the day, particularly as people hunt down the efficiency and convenience they need to manage modern life. But of course, the hyper speed with which consumers interact with QSRs invites something else entirely: a susceptibility to fraud that frequently goes unchecked and costs food merchants a whole lot more than just money. 

When the brick-and-mortar standard of commerce shifted swiftly into a borderless, digital landscape, the need to adapt was at once extreme and impossible to do well. There wasn’t time to build solid, scalable business models that could bridge the gap between online and in-person transactions, leaving on-demand food merchants with a lose-lose choice to make: give up your corner of the market in the pursuit of protection, or choose growth and accept that you’re going to give up a lot of money to fraudsters.   

For QSRs, which rely so heavily on speed, fraud prevention has never really been top of mind anyway. But the real reason isn’t a lack of interest in protecting customers—it’s a lack of options to protect them effectively. Traditional, legacy fraud solutions based on static rules and manual review have never been up to the task of fighting fraud in real time. They’re still not; according to a survey conducted by Sift, 60% of companies using traditional fraud prevention end up blocking legitimate customers. Additionally, the rules aren’t even preventing criminals from organizing attacks; 45% of respondents reported that rules do not effectively prevent fraud. Finally, these solutions require a great deal of human input and manual review, making them slow and inefficient. 

And while it’s true that their snail’s pace takes rules-based fraud mitigation out of the running for QSRs as it is, the bigger problem with these systems—in any industry—comes down to two major insufficiencies: inflexibility and inaccuracy. They put every customer through the same analysis, making them simple for fraudsters to outmaneuver. Customer insult rates go up, too, alongside an uptick in fraud, because even when a trusted user passes most rules, it only takes one failed rule to end their journey on your site. Realistically, most people aren’t going to return to a merchant that gave them a bad experience or that makes them submit verification information every time they try to buy—and that means you don’t just lose a single transaction’s profit. You lose the entire, potential lifetime value of that customer.

If QSRs can’t slow down, fraudsters won’t, and rules-based fraud prevention solutions can’t keep up, what’s an online food merchant to do? 

Sift: Now serving QSRs with Dynamic Friction

For QSR leaders, the answer is becoming clear: to stop fraudsters from eating for free, protect customers, and continue to grow, they must adopt cutting-edge, data-driven technology that can adapt in real time and scale alongside the business. A fraud solution that relies on true, end-to-end machine learning (ML) has the power to do exactly that, giving businesses the ability to differentiate fraud from trusted actions with unmatched accuracy and speed. And, because ML-driven solutions are capable of learning from data and adjusting models in real time, they only become smarter and more beneficial to merchants (and consumers) over time.

In a recent article from CNBC, National Restaurant Association SVP of Research, Hudson Riehle, commented that the quick-service industry has grown faster than sit-down chains for two major reasons. First, that the industry as a whole is being driven forward by convenience and socialization; secondly, that a brand’s reputation is “no longer handcuffed to great service.” There’s far more importance placed, by consumers, on removing friction from the order and delivery experience, upping the speed of the experience from start to finish. 

This is why Dynamic Friction, an approach pioneered by Sift and that enables the creation of custom-tailored experiences for QSRs’ end users, can make such a critical difference when it comes to fighting fraud in real time. At its core, Dynamic Friction allows online businesses to apply friction when it’s needed (e.g., using two-step verification when a transaction is flagged as potentially fraudulent) and remove it when it’s not (e.g., for trusted customers or on recurring payments). Quick-service leaders like Favor Delivery and DoorDash are already seeing the benefits of Sift’s unmatched accuracy, speed, and sophistication.

In our latest ebook, Digital Trust & Safety for QSRs: Turning the tables on fraud, QSR leaders will discover consumers’ top QSR fraud concerns, the biggest fraud threats haunting this space, and how to simultaneously protect diners and business interests against fraud while fueling growth. 

Click here to download the complete ebook.