在动态监管环境中利用AI/ML解决方案应对反洗钱挑战

That's a very real challenge. We've had some success with unsupervised learning models that can identify anomalies in transaction patterns, but the ongoing calibration to minimize false positives is a significant time commitment. Have you found any particular features or data points that are proving most indicative in your crypto AML monitoring?

The 'escalating complexity' is certainly a challenge, and crypto transactions have only compounded it. Most firms I know are still struggling to integrate AI/ML effectively without just shifting the problem to a different part of the compliance team. The false positive rate remains a significant hurdle.