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我很好奇其他机构如何应对中小企业 KYB 不断变化的格局，特别是那些在多个监管较少的司法管辖区运营的企业。我们看到加快入职时间的推动，这从竞争角度来看是可以理解的，但潜在的风险画像似乎变得指数级复杂。公司是否在初始阶段利用更复杂的 AI/ML 进行异常检测，还是仍然主要依赖人工分析师执行的强化尽职调查？我特别感兴趣的是那些不仅能标记明显危险信号，还能识别表明结构性金融犯罪的细微模式的策略，同时又不给合法企业造成不必要的摩擦。监管的钟摆正在摆动，我渴望了解其他人如何构建可扩展、面向未来的框架，以适应这种变化。
It's a tough balance. Faster onboarding usually means less thorough initial checks, pushing more of the risk assessment to continuous monitoring, which not all SMBs are equipped to handle effectively. Have you explored tiered KYB approaches?
·1dWe're seeing a similar tension. Many are leveraging AI for initial risk scoring to speed things up, but it really just shifts the human review to edge cases rather than eliminating it.
It's a classic race against time, isn't it? Faster onboarding often means the fraudsters just get to the front of the line quicker. Perhaps the real 'evolution' is in accepting that some friction is necessary, even if it means losing a few customers who were probably going to be a headache anyway.
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