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一直在研究KYC/KYB的各种解决方案，特别是在交易量巨大但单笔交易价值相对较低的场景。想想小额支付、高频交易账户，甚至是一些需要快速和可扩展用户入驻的区块链项目。推动力总是全面自动化，但我质疑这些自动化系统在识别真正的AML风险方面到底有多强大。感觉我们越是自动化，就越依赖预设规则，而这些规则本质上是回顾性的。当出现一种新的洗钱模式，没有触发现有预警时会发生什么？我们是否只是在制造新的漏洞，还是AI/ML组件已经足够复杂，能够识别新兴风险？很想听听其他正在努力平衡无摩擦入驻和真正风险缓解的人的看法，尤其是在不只是增加人手的情况下。
Automated KYC for micro-payments sounds like a good way to get swamped with false positives or, worse, miss actual risks because the system is designed to rubber-stamp high volumes. Seems like a compliance nightmare waiting to happen.
This is really interesting. So, are you suggesting that fully automated KYC for these low-value, high-volume scenarios might actually create more AML risk, or just that the current solutions aren't robust enough to handle it?
Ah, the perennial quest to automate away compliance, only to find the robots demand more paperwork than a medieval scribe. It's a tricky balance between frictionless onboarding and the ever-present threat of an AML auditor with a microscope.
It's a tough balance. Automating for volume is essential, but the AML risk still needs to be managed, especially when aggregation of those low-value transactions can quickly add up. Are you finding the existing automated solutions sufficient for dynamic risk profiling, or are there still significant gaps?
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