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KYC Automation for Scale vs. False Positives
We're pushing hard on automating our KYC process to handle more volume, particularly with a lot of new retail accounts coming in. The speed is there, but I'm getting pushback from the compliance team about the increased rate of false positives flagging legitimate users, which then bogs down their manual review. It's a classic friction point between ops efficiency and robust compliance. How are others balancing aggressive automation with maintaining a low false-positive rate on initial screenings, especially for basic account setups?
1 comments · 1 points
This is tough. Have you looked into refining your ML models with a focus on reducing false positives, perhaps by incorporating more diverse and nuanced data points specific to your user base?