Why quick-service restaurants have a digital fraud problem
Consumer demand for online and mobile ordering has accelerated significantly. To meet the demand, 31% of restaurants said they’ll invest in delivery services or technology, according to a 2020 Reward Networks survey. And that’s not a bad idea.
Those that plan to adopt online and mobile ordering can recoup more revenue lost to a decline in dine-in customers through things like up-sell opportunities. On average, online orders are 20% larger than in-restaurant purchases, says a recent ChowNow report.
But more online and mobile orders mean an increase in digital fraud losses. Bad actors aren’t just targeting the point of payment. They’re going after many points in the customer journey. For quick-service restaurants (QSRs), solving digital fraud problems means understanding four key elements that contribute to it.
1. They don’t understand what ‘good’ customers look like
It’s key to remember that QSR transactions don’t always look like typical e-commerce transactions. They’re smaller and more frequent.
For example, it’s not unusual for a customer to make several small purchases from a QSR in a day. Those are still “good” customers. Now, compare that to a furniture company or clothing retailer. Several small transactions from one customer in a day may more likely be a bad actor testing credit cards.
QSRs can employ advanced AI and machine learning fraud detection to assess the risk of each transaction. These tools combined produce a safety score almost instantly. QSRs can use that score to understand if those small orders are normal for that customer. As a result, the business can automatically approve the good order or decline fraudulent activity.
2. They’re not protecting customer accounts from account takeover attacks
Customers who use QSR apps accumulate loyalty points and rewards. Protecting those points is essential to keeping good customers and maintaining brand trust. Unfortunately, credential stuffing and account takeover fraud put those points — and revenue — at risk.
Account takeover fraud has emerged as an issue for online businesses and digital commerce. Given that consumers often use the same credentials across multiple sites, bad actors don’t need a lot of data to launch an attack. Just a password, account number, username, email address, or Social Security number will do.
Once an attacker acquires credentials from a website breach or password dump site, they can test them across sites. In these credential stuffing attacks, bad actors try thousands of usernames and passwords quickly to access user accounts and any stored value.
Account takeover can have devastating, long-term effects on QSRs. Beyond lost revenue, account takeover fraud damages brands and erodes the trust of good customers. But an account takeover solution can prevent credential stuffing and account takeover fraud.
An account takeover solution assesses when users are exhibiting abnormal or potentially fraudulent behavior. Once the solution detects abnormal behavior, it can block it entirely or challenge it.
3. They’re taking too long to make decisions
For QSRs, speed and convenience are essential because customers have options. For example, if one restaurant’s app or online ordering platform takes too long to approve a transaction, good customers will be less likely to return.
Any friction in the buying experience can drive customers to competitors and erode loyalty. But having a fraud detection system that uses AI and machine learning can save QSRs valuable time. These tools ensure that good customers get frictionless, personalized experiences, and businesses can accept more good orders and stop fraud losses.
4. They’re not detecting card testing
QSRs are common targets for card testing attacks. Card testing occurs when bad actors need to validate stolen credit card details. To do this, they may place several small orders on one card or many, at once or within a short time frame. Essentially, they’re weeding out canceled or invalid cards. Once they confirm which credit card numbers are active, they can make larger purchases on other sites.
Because QSRs can’t manually review every small transaction, they need a fraud detection system that does the hard work for them. A system that learns on a global data network can use billions of data points to understand the difference between normal and fraudulent activity.
QSRs alone may not know much about a customer’s buying activity. But a global data network pulls data from across industries, so QSRs have a more accurate idea of what abnormal behavior looks like.
Protect the entire customer journey to solve your digital fraud problem
These days, it’s too easy to lose customers to the competition. QSRs and fast-casual restaurants moving into the card-not-present space are learning what e-commerce retailers discovered years ago. When bad actors attack, the losses add up quickly. The good news is that enterprise fraud solutions worth their salt are ready to fight fraud in the restaurant space.
Kount’s combination of human expertise, advanced AI, and machine learning makes it easy to serve up certainty in every digital interaction. As a result, Kount can help QSRs protect and manage the entire customer journey — from account creation and login to loyalty redemption and checkout.