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AI Scams Target Trust Before Transactions - Visa DPS - News Directory 3

AI Scams Target Trust Before Transactions – Visa DPS

September 12, 2025 Victoria Sterling Business
News Context
At a glance
  • This article argues that traditional fraud prevention‍ methods, which focus on stopping fraudulent transactions, are no longer sufficient.
  • * Fraudsters are⁤ collaborative: ⁤ They readily share intelligence and tools, giving ‌them an advantage over individual financial institutions.
  • In essence, the article advocates for a move from reactive fraud⁢ detection to proactive ‌fraud prevention through enhanced intelligence‌ gathering and analysis.
Original source: pymnts.com

Summary of the‌ Article: Shifting the Focus in Fraud Prevention

This article argues that traditional fraud prevention‍ methods, which focus on stopping fraudulent transactions, are no longer sufficient. The key takeaway is that financial institutions need to shift their strategy‌ to intercept ⁢fraud before money moves, by building a more‌ extensive understanding of risk ⁢throughout ⁣the​ customer journey.

Here’s ‌a breakdown of the main points:

* Fraudsters are⁤ collaborative: ⁤ They readily share intelligence and tools, giving ‌them an advantage over individual financial institutions.
* Transactional security ⁤is not enough: While vital, relying solely on stopping transactions is a losing battle. ⁢It’s difficult ‌to overcome the trust a fraudster has ⁢already‌ built with a consumer.
*⁢ Proactive intelligence is crucial: Institutions need⁤ to gather and analyze data from the entire customer lifecycle – submission, ⁣login, early ‌account use – to identify risks early ⁤on.
* ⁢ Unified data is key: Connecting disparate data points (application details, device details,‌ bureau checks, threat​ intelligence, behavioral signals) into‍ a single, actionable view is essential.
* Behavioral data is ​valuable: ‌Mobile and login data provide rich insights into user behavior that‌ can help identify fraudulent activity.

In essence, the article advocates for a move from reactive fraud⁢ detection to proactive ‌fraud prevention through enhanced intelligence‌ gathering and analysis. The goal is to “surface the risks before⁤ they manifest” ​and ‌engage with fraudsters on their ‍battlefield, rather‌ than waiting ​for the​ final ⁣stage of the attack.

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