There are a lot of reasons for a business to suspect fraudulent activity is happening. Maybe a delivery address is in a country that doesn’t match the cardholder’s billing address. Maybe a frequent customer is placing a higher-than-average order. Maybe orders are coming in quick succession with lower-than-average purchase denominations. Taking chances on those orders could lead to fraud. But declining those orders could lead to false positives.
Most commonly, false positives in fraud detection occur when a business declines a legitimate order due to suspected — but not confirmed — fraudulent activity. And whether you call them false positives, sales insults, customer insults, or false declines, rejecting legitimate orders can have long-term consequences. Not just revenue loss, false positives impact key areas in the digital customer journey and affect a customer’s lifetime value, acquisition costs, and trust in a brand.
Let’s take a closer look at how false positives disrupt the customer’s digital journey and affect businesses long-term, as well as three ways to prevent them.
False positives disrupt the digital customer journey and increase friction
A customer’s digital journey includes five essential steps, as outlined by Casey Zenner, Kount’s Director of Enterprise Sales, at Kount’s Fall 2020 Digital Protection Summit. Those five steps include awareness, consideration, acquisition, service, and loyalty. And while all of them are important, businesses are most likely to experience false positives at the acquisition stage.
In the acquisition stage, good customers create accounts or login to existing accounts. They’ve gone through the awareness and consideration stages, so they’ve acknowledged that they want to buy something and navigated their options across websites. In reaching the acquisition stage, customers signal their intention to place items in their carts, proceed to checkout, and place an order. In the digital customer journey, these orders are generally card-not-present (CNP) transactions.
Unfortunately, false positives disproportionately affect card-not-present (CNP) transactions, according to a 2019 Aite Group report. The report found that the average card authorization rate is 97% for point-of-sale transactions but falls between 80% and 85% for CNP transactions. Overall, the length of a customer’s journey depends on the business or industry. The digital journey to buying a pizza is longer than the journey to buying a new TV, for example. But businesses that aren’t considering all the time it takes for customers to reach the acquisition stage are introducing friction — and leaving money on the table.
False positives have long-term effects on businesses
Businesses have a lot to lose in false positives. Just one false positive can deter good customers forever. In fact, 25% of Americans say they would not return to a website if it turned them away from a legitimate transaction. They would take their business elsewhere, according to insights from Kount’s 2020 Holiday eCommerce Guide. Aside from losing customers, false positives harm online businesses financially in four fundamental ways:
- Immediate revenue loss. Among businesses that track false positives as a key metric, 60% estimate their false-decline rate is between 1.1% and 5%, according to the Aite Group. By those figures, a business that makes $50 million in annual revenue stands to lose up to $2.5 million of it to false positives.
- Lost customer lifetime value. Lifetime customer value is the total profit a business anticipates from all future purchases by a customer. Legitimate customers who are wrongly declined may stop buying from that merchant altogether.
- Wasted acquisition costs. Acquisition costs are what a business pays to convince a consumer to place an order. That includes targeted research and advertising. For example, if a business spends $100 to take a customer through to the acquisition stage in their journey and declines that customer’s order, they lose revenue and the $100 in advertising.
- Brand damage. In today’s world of social media and viral word-of-mouth, one shopper’s experience with a false positive can reach thousands of existing and potential customers and potential customers.
3 tips to reduce false positives throughout the customer journey
What a business suspects is fraud depends on its sales model, industry, and customer buying habits. But any business that isn’t tracking false positives can’t say, for sure, how much they’re losing to them. Businesses that track false positives rely on customers to inform their numbers, according to the Aite Group. 80% identify a false positive if a customer makes a second successful attempt at the purchase. Another 56% only rely on the customer to contact them. Take the guesswork out of approving or declining orders and follow these three tips to reduce false positives.
1. Change your mindset about false positives
Aite Group estimates that false positives in the U.S. will cost businesses $443 billion by 2021, over $100 billion more than the 2018 estimate. That’s a lot to lose on the fear of fraud, the suspected cases of fraud. In many cases, false positives go unnoticed because online businesses think more about preventing fraud than losing sales. But that’s not always the best approach. The key is to find reasons to approve an order, not find reasons to decline an order.
The first step in reducing false positives is not categorizing false positives as fraudulent orders outright. Once a business shifts how it tracks false positives, it can dig deeper into its false-positive rates. Plus, it can review customer data to determine what normal orders look like, and use AI built on a robust data network to help auto-approve legitimate orders.
2. Implement a fraud prevention solution that uses AI and machine learning
AI and machine learning use massive computing and memory capabilities to analyze billions of data points, detect associations, weigh probabilities, and quantify risk in milliseconds. This allows fraud prevention systems to go beyond mere detection and take fraud prevention to the next level: prediction.
“A fraud prevention solution that employs machine learning can reduce false positives because it allows the solution to find what looks like a good order versus a bad order,” Gabiou said.
When businesses implement AI and machine learning into their fraud prevention strategies, they can access a network of data that can enhance fraud detection, increase order approvals, and decrease fraud risk.
3. Protect the entire customer journey with the Identity Trust Platform
More than just preventing fraud, businesses need to establish identity trust at every stage of the customer journey. An identity trust platform establishes the level of trust for each identity behind payments, account creations, and login events.
“You need to make sure your risk strategy isn’t preventing good customers from buying goods and services,” explained Zenner. “The bulk of the conversations we’re having prospective enterprise customers is around combating false positives, improving those acceptance rates while keeping chargeback rates at or below industry benchmarks.”
Kount’s Identity Trust Platform is industry-leading protection for the entire customer journey, from account creation and login to payments and disputes. Linked by AI, Kount’s Identity Trust Global NetworkTM combines trust and fraud signals from 56 billion annual interactions to block fraud in real time and enable personalized customer experiences. Quick and accurate identity trust decisions deliver safe payments and account creation and login events while reducing digital fraud, chargebacks, false positives, and manual reviews.