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Broadcom Introduces Arcot Scam Defense to Combat Social Engineering Fraud

Broadcom Introduces Arcot Scam Defense to Combat Social Engineering Fraud

First seen 21 Oct 2026, 15:41 UTC • •

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ThreatCluster AI
ThreatCluster •October 21, 2026 at 17:09 UTC
  • •Broadcom's Arcot Scam Defense targets social engineering fraud in CNP transactions.
  • •The feature flags potential fraud post-authentication by analyzing multiple data signals.
  • •Pilot testing suggests significant fraud prevention potential, with $4 million protected monthly.

Broadcom has launched Arcot Scam Defense, a new feature aimed at preventing social engineering fraud during card-not-present (CNP) transactions. This feature analyzes transaction data, device information, and user behavior to flag potential fraud even after successful authentication challenges. Matt Cooke from Broadcom highlighted that financial institutions are facing a surge in fraud attempts, particularly those enhanced by AI. The feature aims to protect cardholders by detecting anomalies that indicate a scam, such as inconsistencies between devices used for authentication. In pilot testing, it was estimated that reviewing just the top 1% of successful challenges could prevent approximately $4 million in fraud over one month. Broadcom reported nearly $500 million in fraud from authenticated challenges over the past year. The Arcot Scam Defense integrates with third-party tools to enhance detection capabilities.

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Timeline

2026-10-21
Broadcom announces Arcot Scam Defense launch
Broadcom introduced Arcot Scam Defense to combat social engineering fraud in CNP transactions.
Stocktitan
2026-10-21
Pilot testing results disclosed
Broadcom estimated that reviewing the top 1% of successful challenges could prevent $4 million in fraud monthly.
Thepaypers

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Common questions

How does Arcot Scam Defense work?
It analyzes transaction data, device intelligence, and user behavior to detect potential fraud even after successful authentication.
What is the estimated impact of this feature?
Pilot testing indicated that it could prevent around $4 million in fraud monthly by reviewing the top 1% of successful challenges.
Who is affected by this type of fraud?
Cardholders engaging in card-not-present transactions are primarily at risk from social engineering scams.