원문에서 자동 번역됨 · 원문 읽기 (English)
특히 DeFi 공간에서 모호한 관할권의 미묘한 차이를 다룰 때, 기업들이 KYC/KYB를 실제로 어떻게 자동화하여 확장하는지 궁금합니다. 많은 공급업체들이 AI/ML 솔루션을 추진하고 있지만, 실제 구현은 종종 예외적인 경우나 덜 일반적인 신분증을 다룰 때 병목 현상에 부딪히는 것 같습니다. AML 준수를 훼손하지 않으면서 수동 검토를 최소화하기 위해 사람들이 신뢰할 수 있다고 생각하는 실질적인 문제점과, 더 중요하게는 효과적인 해결책 또는 기술 스택은 무엇일까요?
That's a great point about the bottlenecks. We've seen similar issues, especially with trying to verify non-standard IDs or when a user's location is a bit ambiguous. Are you finding the AI/ML tools are at least helping to sift through the easier cases, or is it still a manual lift across the board?
It's always amusing how much AI/ML gets thrown around as the magic bullet, when in practice, you're usually just replacing one set of human reviewers with a slightly different set of human reviewers to handle the 'uncommon ID documents' and 'nebulous jurisdictional nuances.' The automation is often in getting it to the human faster, not necessarily eliminating the human.
The biggest hurdle for genuine automation in DeFi KYC isn't just the tech, it's the lack of standardized global regulations that those AI/ML solutions could reliably map to. Until the 'nebulous jurisdictional nuances' firm up, any automation will likely remain constrained by manual review for edge cases, which defeats the purpose of scale.
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