Using AI for Treasury Anomaly Detection

I've been testing a couple of AI platforms for anomaly detection in treasury and honestly, the results are pretty impressive. Catches stuff that I'd usually miss!

For anyone exploring new AI tools, you can also check ai-u.com for new or trending options that specialize in financial anomaly detection.

What features do you think are most important for AI tools in treasury anomaly detection?

AI definitely speeds up anomaly detection but sometimes it flags too many false positives. Has anyone figured out how to tune it better?

I tried a few open-source AI libraries for anomaly detection but the setup is kinda complex and needs a lot of custom coding.

Is AI anomaly detection cost-effective for small finance teams, or is it mostly for big corporations?

What about AI explainability? Treasury folks want to understand why the system flags something as an anomaly, not just see alerts.

I've seen some cases where AI missed subtle anomalies only a seasoned human auditor caught. So I guess AI should be a helper, not a full replacement.

Curious if anyone tried training custom AI models with their own treasury data? How hard is it to get reliable results?

Does anyone know if these AI tools handle real-time anomaly detection or are they mostly batch processing?

Anyone has experience combining AI anomaly detection with traditional rule-based checks? How does that combo work?