AI use case / Banking & Financial Services
AML Investigation Workflow
AML investigators manually resolve entities and assemble evidence across transaction and research systems.
Design this AI workflowWhy this workflow
Make the next decision faster.
AML investigators manually resolve entities and assemble evidence across transaction and research systems.
The workflow
From signal to supervised action.
The exact implementation changes by organization. The operating pattern stays clear.
Built with control
Autonomy is useful when the boundary is clear.
CodeCrux designs the workflow around its permissions, review points, system actions, and evidence requirements.
Frequently asked questions
Questions teams ask before they build it.
What is AML Investigation Workflow?
AML Investigation Workflow is a multi-agent system for compliance teams in Banking & Financial Services. It helps address this problem: AML investigators manually resolve entities and assemble evidence across transaction and research systems.
How does AML Investigation Workflow work?
The workflow starts when aml alert is raised. It uses entity resolution, transaction graph and evidence agents to complete these steps: Resolve related entities; Analyze transaction relationships; Retrieve historical investigations; Search approved adverse information; Compile evidence for investigator review.
What systems can AML Investigation Workflow connect to?
A typical implementation can connect to approved systems such as Transaction platform, Case management, KYC data, Research sources, Entity graph. The exact integration depends on the organization's architecture, access policies, and data boundaries.
What should humans approve in AML Investigation Workflow?
Human involvement should remain where the workflow requires judgment, exceptions, or a sensitive business action. For this use case, Review the case, apply judgment and decide escalation or reporting.
What controls are needed for AML Investigation Workflow?
Important controls include Source authorization, Evidence provenance, Investigator approval, Retention policy, Auditability. These controls help define what the AI system can see, recommend, or do and when a person must review the outcome.
Is AML Investigation Workflow ready for production?
This workflow is marked advanced in the CodeCrux use-case library. Production readiness still depends on data quality, system access, evaluation, observability, security, and a clear human review design.