> ## Documentation Index
> Fetch the complete documentation index at: https://docs.insightsecure.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# AML Case Investigation — Overview

> Mule-account detection and investigator workflows

AML Case Investigation is built for compliance and financial-crime teams who need to go beyond a single transaction alert — investigating an **account's behavior in the context of its network**, over time, and building a case file that holds up to a regulator.

<CardGroup cols={2}>
  <Card title="Mule graph detection" icon="diagram-project" href="/aml/mule-graph-detection">
    Network-graph analysis surfaces mule-account rings — fan-in/fan-out money-movement patterns that look unremarkable transaction-by-transaction but are obvious once graphed.
  </Card>

  <Card title="Self-learning feedback loop" icon="arrows-rotate" href="/aml/self-learning-feedback-loop">
    Every analyst decision (confirmed mule, false positive) feeds back into the model via continuous backtesting — detection improves from real outcomes, not just periodic manual retraining.
  </Card>
</CardGroup>

## How it fits with Device Intelligence

The same device and user graph that powers Device Intelligence's [device-to-user mapping](/device-intelligence/beyond-rasp#device-to-user-graph-mapping) is available to AML investigations — an account flagged for mule activity that also shares a device with several other flagged accounts is a materially stronger case than either signal alone.

## Who uses this

<CardGroup cols={2}>
  <Card title="AML/CFT analysts" icon="user-magnifying-glass">
    Work cases in the investigation console — graph view, transaction timeline, and evidence collection in one place.
  </Card>

  <Card title="Compliance officers" icon="clipboard-check">
    Review case dispositions, export evidence for regulatory filings (STR/SAR-equivalent), and track model performance over time.
  </Card>
</CardGroup>