Step 1
Core banking data
Accounts and transactions, read nightly
← Solutions Lab · Accelerator
Accelerator
QAO MuleShield Connect
A connector that lets cooperative and small banks detect mule accounts and act on the results.
INDUSTRY BFSISOLUTION FAMILY Enterprise Integration and Automation
The problem it solves
Mule accounts move fraud proceeds through the banking system. National authorities want every bank to detect them, but cooperative banks and small banks often lack the data teams and modern systems to connect.
How it works
Four steps. A person decides.
Step 2
Feature pipeline
Data prepared in the shape detection models need
Step 3
Scoring connector
Any approved mule-detection model or service
Step 4
Investigation and action
Linked accounts, money flows and officer approvals
What's inside
Built for the real work.
Core banking adapters
Works with the core systems small banks actually run.
Model-neutral scoring
Connects to an approved national model or the bank's own.
Network view
Linked accounts and money flows shown as one picture.
Officer approval
Holds and freezes recommended, never applied automatically.
Built with
Data pipelineGraph analyticsScoring API connectorPythonPostgresReact
Related
Use cases and case studies.
Use Case
Fraud and mule detection for small banks
Explore the use case →Case Study