Nasdaq Verafin Takes the Fraud Fight to the Dark Web
Banks often don’t see a fraud scheme until money has left the account, and then it’s too late. A stolen check, compromised card or banking credential may already have circulated among criminals, giving fraud teams little time to intervene. As payments move faster and fraudsters gain tools that make it easier to exploit stolen information, […] The post Nasdaq Verafin Takes the Fraud Fight to the…
Banks often learn about fraud schemes only after money has been transferred, leaving little opportunity for intervention. Colin Parsons, head of fraud product strategy at Nasdaq Verafin, explained to PYMNTS that most of the fraudulent activities occur outside the banking system. The challenge is that fraud becomes visible to institutions only when a transaction occurs or money moves.
Nasdaq Verafin and Q6 Cyber are partnering to address this issue by providing financial institutions with intelligence gathered from online criminal activity. The focus initially includes compromised checks, payment cards, and online banking credentials. This approach aims to alert institutions about compromised accounts before any transaction occurs.
Fraudsters are increasingly adopting artificial intelligence, especially in crafting more convincing attacks, such as using large language models to automate social engineering and defeat financial institutions' fraud controls. Compromised checks, cards, or bank credentials contain sensitive account information that can help criminals impersonate individuals or businesses.
Q6 Cyber CEO Eli Dominitz highlighted that this information can explain why impersonation attacks are sometimes remarkably specific. By providing this information before a transaction, financial institutions can take protective measures or contact customers, disrupting the fraudulent activity. The partnership between Nasdaq Verafin and Q6 Cyber combines their views of the fraud cycle.
While Q6 Cyber focuses on activity outside the financial institution, Nasdaq Verafin brings those signals into its transaction and counterparty information network. This collaboration gives investigators an external view alongside their internal data. Detecting fraud early can minimize transaction disruption and allow institutions to act selectively, rather than applying broad controls to all transactions.
Additionally, the use of AI in processing this intelligence helps investigators prioritize alerts and focus on the most critical matters, reducing noise and improving efficiency.
Written by urgent.news from PYMNTS's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
