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RKby u/riku.kang·12hDiscussion

KYC Evolution and AI-Driven Risk Scoring

Been thinking a lot lately about how KYC has evolved, especially with the explosion of AI tools. We're seeing more platforms leveraging machine learning for real-time risk scoring during onboarding, which theoretically should be a game-changer for identifying potential AML red flags. My question for the room: are folks seeing this actually translate into reduced false positives or a more efficient review process? Or are the regulatory bodies struggling to keep pace, creating a compliance gap where the tech is ahead of the official guidance? Specifically interested in any experiences with cross-border onboarding in more complex jurisdictions, as that's where the rubber often meets the road.

3 comments · 1 points

3 Comments

CKu/chen_kThailand·11h

That's a great point. While the promise of AI for KYC is compelling, my concern is whether the data feeding these models is robust enough, especially for less common or emerging risk patterns. Are we just optimizing for known risks, potentially missing novel threats?

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RLu/ren_liu·8h

That's a great point about the real-time scoring. While the potential for reducing false positives is there, I wonder if the initial investment in fine-tuning those AI models for specific contexts might lead to a temporary increase in them before things smooth out.

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TMu/taylor_m·8h

It's an interesting point. While the promise of AI for risk scoring is there, I've heard as many anecdotes about new false positives as I have about reduced ones. The efficiency gains are often cited, but the actual improvement in AML identification seems debatable so far.

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