$362 billion in fraud: How insights can help reduce losses — and improve the digital experience

As the impact of fraud grows, consumers are, understandably, growing more careful. A resounding 91% say they would consider abandoning a company altogether if they experienced fraud while making a purchase, according to a recent Mastercard report.

Merchants are cautious, too: The same research finds that nearly four in 10 merchants worry about being classified as high risk from fraud, as financial institutions often charge higher fees in response.

A high-wire act between convenience and safety

What complicates growing fraud is that convenience still matters — a lot.

Our research reveals that over a quarter (28%) of consumers have abandoned a transaction out of frustration with how long it took to enter their details. And their expectations around agility are likely to remain high: Gen Z consumers are almost 2.5 times more likely to desire a speedy online purchase journey than Baby Boomers, for instance.

Still, striking the right balance between security and convenience is not a simple 50/50 split. The same report suggests that most shoppers (77%) prioritize security over speed during online transactions.

So, how can businesses deliver a smarter, more secure user experience? The most forward-thinking organizations are leveraging and actioning on data and insights to improve their fraud prevention tactics.

How robust insights lead to faster checkouts, less friction and safer transactions

For today’s businesses, the real competitive edge comes from using insights intelligently and putting the right parameters in place to seamlessly authenticate transactions that are, indeed, genuine.

With fraudsters employing increasingly sophisticated methods — including those powered by AI, which can create new attack vectors for bad actors — businesses must rely on more than just the set rules that have worked in the past. The future lies in contextual intelligence and identity insights: understanding how pieces of information connect, how patterns deviate from the norm, and how to interpret subtle signals in real-time.

Take a transaction with an email address from john.doe@gmail.com. Drawing on insights from previous transactions, an AI-powered system can identify if the email has been recently created, indicating possible fraudulent activity, or if it is a long-standing, more trustworthy email address.

To create a more secure transaction experience without sacrificing agility, businesses must leverage a combination of machine learning, historical patterns and real-time insights. Here are some common types of insights that can help make it happen:

1. Person capabilities: By analyzing common identifiers like names, emails, addresses and phone numbers in the right context, businesses can capture insights into those identifiers that can help inform their decision on whether to move ahead and confirm a digital interaction. Here are three important things to consider, especially regarding new users:
   • Email: Is the email address recently created, or has it appeared in legitimate transactions before?
   • Name: Has this person’s name been previously linked to this email or shipping address?
   • Phone number: Is the phone number consistent with past purchase behavior, or has it been flagged in prior fraud attempts?

   These insights, when combined and analyzed, can assign a score that reflects the overall risk of a transaction. A higher risk score doesn’t necessarily mean the occurrence of something malicious — but it might warrant a closer look to examine the insights used to make that determination.

   The good news is that merchants can build automated actions based on each score, meaning more secure transactions get through, while potential fraudsters encounter additional rounds of authentication.

2. Behavior capabilities: This type of information refers to how someone interacts with a site or service. With the right tools, it can often be more telling than the direct information they provide. Here is a potential red flag to watch out for:
   • Transaction value and volume: Is the size or frequency of a transaction out of character for this particular user?
   AI and machine learning models learn from these patterns, flagging behaviors that deviate sharply from expected norms. Over time, they get smarter — distinguishing between a late-night gift purchase and a fraudster operating through a false identity.

3. Device capabilities: The type of device a consumer uses to access a business’s service, such as a phone, tablet or computer, can offer critical insight into legitimacy. Businesses should keep track of:

   • Consistency: Is the consumer’s device the one usually used by this account?
   • Device type: Is the operating system or browser outdated, rooted or known to be associated with fraudulent activity? For example, an Android device displaying a user agent with an Apple iOS Safari browser could be a cause for concern.

Employ a holistic view

Together, these types of insights can be fed into a real-time risk model. A minor discrepancy might pass unnoticed — but stack enough inconsistencies, and they will reflect in risk scores.

Ultimately, businesses must decide how to implement these insights to enrich their fraud decisioning. For instance, a phone number and IP mismatch — a relatively common occurrence — would not stop a transaction from proceeding as usual, while certain fraud patterns could trigger two-factor authentication or a temporary hold.

These layers of intelligence allow businesses to build a seamless experience that’s both secure and efficient. Instead of placing the burden on customers, modern fraud tools use insights to verify legitimacy behind the scenes — providing genuine transactions with faster checkouts, while stopping bad actors before they do damage.

The battle against fraud isn’t a zero-sum game

With the interconnectedness of today’s ecosystems, sophistication of attacks, accessibility of fraud services and believability of schemes and scams, businesses may feel like they are walking a tightrope between safety and convenience. But it’s the responsibility of all businesses to protect consumers and ecosystems at scale — and they can, so long as they’re equipped with the right strategies.

By leveraging more robust insights from online interactions, businesses can streamline user experience from login to log out. These stronger, measured data insights can also lead to faster transaction approvals, higher revenue and better customer experiences that inspire loyalty.

The opportunity is clear, the solutions exists and the clock is ticking. There’s no better time to begin than now. Access our resources for trusted transactions to help minimize fraud, maximize approval rates and ensure better decision-making.