Exclusive: Visa sets up new team to take down all scammers
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Illustration: Sarah Grillo/Axios
Visa has created an unprecedented scam detection initiative, built to both protect customers and dismantle the scammer ecosystem, the company shared exclusively with Axios.
Why it matters: Consumers lost more than $1 trillion to scams around the world last year, according to a report from Feedzai — but few resources exist to adequately fight back against the vast online scam ecosystem.
- Visa's approach could serve as a blueprint for other companies looking for ways to fight scammers.
The big picture: Like ransomware gangs, online scammers run vast, international operations — but instead of extorting corporations, they exploit individuals on a massive scale.
- Romance scams, phishing emails, and payment fraud are all part of the scammer ecosystem.
- Fraudsters are increasingly using generative AI to write convincing phishing emails, improve deepfakes, and draft new forms of malicious code — making scams harder to detect.
Between the lines: Law enforcement can't handle the volume of online scams, so private companies need to step up.
How it works: Visa's new scam detection practice is modeled after threat intelligence units inside cybersecurity companies, which proactively study and research threat actors to prevent new attacks.
- Visa has invested $12 billion over the last five years to improve its cyber, fraud, and risk tools. The scam disruption practice is part of that broader effort.
- The new practice includes an intelligence team that goes beyond Visa's own payment network and studies the dark web and social media to uncover scammers' actions, Michael Jabbara, senior vice president of payment ecosystem risk and control at Visa, told Axios.
- Visa also has a dedicated disruption team that partners with industry peers and law enforcement to shut down scam networks, including fraudulent merchant sites and scammers' financial accounts found on Visa's networks.
- Employees on the team come from a mix of backgrounds, including cybersecurity, fraud detection, data science, and law enforcement, Jabbara added.
What they're saying: "Consumers can only do so much, we need to also be there to protect them and help level the playing field a little bit," Jabbara said. "They're not going to stand a chance if you don't have folks who are standing behind their back."
The intrigue: Visa estimates its team, which it has been building over the last year, disrupted more than $350 million worth of attempted fraud in 2024.
Zoom in: Last year, the new Visa team took down roughly 12,000 merchant websites linked to a fake background check scam on dating apps.
- Scammers posed as real people, built rapport, and then asked victims to run a background check before meeting.
- The fraudulent website signed victims up for recurring payments that often went unnoticed, Jabbara said.
- Visa found that the 12,000 fraudulent merchants were spread across more than 10 financial institutions and two continents. The company estimates this takedown prevented more than $27 million in victim losses.
- "We can actually find that needle in the haystack — but then we can connect that needle to all the other needles and all the other haystacks that are set up all around the world," Jabbara said.
Reality check: Visa has a vested interest in ensuring that fraud doesn't continue to target their customers or its own platforms.
- Each time a customer's payment is returned, Visa incurs operational costs for those transactions and spends its own resources investigating customers' claims.
- A high volume of fraud-related chargebacks can also make Visa's network look riskier, potentially leading to more regulatory scrutiny or pressure from financial institutions.
- By establishing itself as a leader in this space, Visa could benefit from stronger relationships with banks, merchants and regulators.
What's next: Over the next year, Visa is focused on expanding its intelligence-gathering and speeding up scam takedowns. And the practice is investing more in generative AI and automation to scale its scam detection, too.
