In today’s LinkedIn post, I explored key takeaways from a webinar on "Unveiling Britain's Fraud Landscape: Harnessing Human-Machine Harmony to Combat Scams by IDnow."
The discussion highlighted the importance of collaboration between humans and technology in fraud prevention, and this principle applies strongly to Anti-Money Laundering (AML) compliance as well.
This leads us to a crucial question:
If I cannot rely solely on AI for AML compliance, then why use it at all?
The Answer
There's a key distinction between relying on AI for AML and using AI as a tool for AML. Here's the difference:
Relying on AI for AML: This implies complete dependence on AI to identify and flag suspicious activity. While AI can analyze vast amounts of data and detect patterns that humans might miss, it lacks the critical thinking and investigative skills needed for thorough AML compliance. Solely relying on AI could lead to missed red flags or even false positives, wasting resources on investigating non-threatening cases.
Using AI as a tool for AML: This approach leverages AI's strengths while acknowledging its limitations. Here's how entities use AI without relying on it:
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