Visa Says AI Isn’t Enough to Stop New Wave of Scams

Watch more: Visa Protect With Aman Cheema

In financial services, deception travels as quickly as money itself, forcing financial institutions to confront scams that exploit both digital systems and human psychology.

That shift formed the focus of a recent PYMNTS interview with Aman Cheema, vice president, head of Global Professional Services, Risk and Security Intelligence Solutions at Visa. The discussion, part of the “Visa Protect” series, examined how banks, merchants and payment networks are rethinking fraud prevention as criminals deploy increasingly sophisticated tactics.

AI Is Table Stakes in Fraud Defense

Artificial intelligence now sits at the center of modern fraud prevention. Yet Cheema cautioned that its widespread adoption means institutions can no longer rely on AI alone to differentiate their defenses.

In his discussion with PYMNTS, Cheema noted that financial institutions have access to the same tools that criminals increasingly use themselves. That reality has reshaped the competitive landscape of fraud prevention. As AI tools proliferate across the payments ecosystem, institutions should pair those capabilities with human judgment and coordinated intelligence to attempt to stay ahead of fraudsters.

The ultimate objective remains straightforward. Financial institutions should ensure that money moves safely while preserving the trust that underpins digital commerce. AI can analyze transactions and identify anomalies but maintaining that trust requires understanding the context and intent behind payment activity.

Technology therefore serves as a component of an anti-fraud arsenal. When paired with experienced risk experts, financial institutions can expand and enhance their fraud capabilities to be more effective at identifying suspicious activity before funds disappear.

Scams Exploit Speed and Human Behavior

Modern scams differ from traditional fraud in both structure and velocity.  New and emerging infrastructure allows criminals to move funds immediately once a victim authorizes a transaction.

“The payment method of choice being used is typically a faster payment rail,” Cheema said, noting that scammers can initiate a transfer and move funds beyond recovery within moments.

He added that the immediacy of these systems creates a narrow window for institutions to intervene.

“The scammers can do whatever is in the armory to get the scam [successfully completed], and the money’s taken instantly and it’s gone. To get that money back proves to be very difficult,” the executive told PYMNTS.

The human dimension further complicates detection. Rather than exploiting technical vulnerabilities, scammers frequently manipulate victims into authorizing the payment themselves.

Generative AI has intensified that challenge. Criminals now use AI tools to gather personal information, mimic trusted contacts and craft persuasive communications designed to convince victims that a transaction is legitimate.

“They’re using the technology in multiple ways,” Cheema said.

Because these scams rely on social engineering rather than stolen credentials, they often appear legitimate to automated monitoring systems.

For issuers, acquirers and merchants, that reality underscores the need to examine transactions within the broader context of customer behavior.

Behavioral Data Helps Identify Suspicious Signals

Data analysis remains a central component of fraud detection, particularly when institutions examine payment behavior over time.

Adaptive behavioral analytics from Featurespace, a Visa solution, helps analyze transaction patterns and develop behavioral profiles that reflect how customers normally use their accounts. Rather than focusing exclusively on individual transactions, the technology evaluates whether activity aligns with established patterns.

“We model your behavior on your payment transactions,” Cheema said, noting that systems analyze purchasing patterns to understand what a customer’s normal behavior looks like.

If a customer who regularly purchases groceries from a familiar location suddenly initiates a significantly larger transaction from an unfamiliar device or location, the system may flag that activity for review.

Yet Cheema emphasized that the challenge lies not in accumulating data but in identifying the signals that genuinely matter. “There’s a lot of data out there. There’s also a lot of noise,” he said.

Filtering meaningful signals from that noise requires sophisticated analytics and a broader ecosystem approach. Shared intelligence among issuers, merchants and payment providers can help institutions detect coordinated fraud campaigns more quickly and respond before they spread.

Human Expertise Provides the Decisive Advantage

Despite advances in analytics, Cheema argued that the decisive edge often comes from human risk experts who interpret emerging patterns and respond quickly.

“The edge isn’t more data,” he said. “It’s who can make sense of that data in a very fast way.”

In many cases, experienced analysts identify connections across transactions, regions or merchant categories that automated systems have not yet recognized. That capability becomes particularly important during coordinated scam campaigns.

Cheema described situations in which organized groups launch attacks targeting specific customer profiles or regions. By examining signals across geographies, investigators can detect those campaigns early.

“You see patterns in one part of the world which make you immediately think that if they’re attacking that profile, there’s a very high likelihood they’re going to be attacking the same persona profile in another part of the world,” Cheema said.

Once analysts identify those patterns, institutions can adjust defensive measures in real time and alert affected organizations across the payments ecosystem.

Human oversight also plays an essential role in coordinating responses. Visa’s fraud specialists may contact issuers, merchants or acquirers directly to confirm suspicious activity and provide guidance during a potential attack.

Cheema summarized that approach as a new operating model for fraud prevention, one that combines “humans, applications and data,” each strengthened by AI.

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