Mule Actioning

Mule detection is being solved at system level. The Reserve Bank’s MuleHunter.AI is effective, supplied free to banks, and spreading fast. What has not been solved is everything that happens next: investigating the flag, mapping the network behind it, deciding the action, recording the evidence and making the filing. Detection volume is now rising faster than the capacity to act on it. The bottleneck has moved from the model to the floor.

• 01Takes detection output from any source (MuleHunter.AI, an in-house model, or your existing monitoring system) and turns it into one prioritised, actionable queue.
• 02Maps the network behind a flagged account: linked accounts, shared devices, funding chains and beneficiary overlaps.
• 03Assembles the investigation pack automatically (transaction evidence, relationship graph, prior alerts and case history) in one place.
• 04Runs the actioning workflow to SLA, from freeze to closure to report, with a complete audit trail behind every decision.
• 05Closes the loop into reporting, so the law-enforcement response and the filing reuse the same evidence rather than rebuilding it.

• Time from flag to action
• Proportion of flagged accounts actioned inside SLA
• Investigations closed per analyst per day
• Completeness of the evidence pack at the point of filing
• Repeat exposure through linked accounts missed on the first pass