What’s inside?
This playbook helps fraud, BSA/AML, and risk leaders understand how a more connected approach to risk can bring fraud, AML, and member intelligence together — improving detection, investigations, efficiency, and the member experience.
- Why fragmented fraud and AML programs can leave important risk connections hidden and create duplicate investigative work.
- How a unified member view connects identity, devices, behavior, transactions, and relationships to provide broader risk context.
- The six components of a modern FRAML architecture, from data orchestration and entity resolution to detection, decisioning, investigation, and reporting.
- How connected analyst workspaces, network intelligence, and AI-assisted investigations can reduce manual work while keeping analysts in control.
- Seven principles for building a unified FRAML program, plus a practical 90-day roadmap for getting started.
- A readiness checklist to assess how connected your current risk program is and identify where opportunities for greater integration remain.
Chapter 1
The Fragmentation Problem
Fraud and AML have traditionally operated as separate functions, with their own responsibilities, technologies, and workflows. However, the risks credit unions face are increasingly connected. An account takeover can lead to illicit funds being moved, a synthetic identity can become part of an organized fraud ring, and a legitimate member account can later be used as a money mule. When these activities are evaluated separately, important connections can be missed. Seeing the broader pattern requires fraud and AML teams to have access to the same intelligence and context.
The operational cost
When fraud and AML operate in separate systems, analysts often spend time collecting the same member information, investigating related alerts independently, and piecing together evidence from multiple sources. This can also create overlapping technology costs and make it harder to see risk across payment channels. FRAML addresses these gaps by creating a shared layer of risk intelligence that connects data, relationships, and signals across fraud and AML workflows. The goal is not simply to consolidate software or combine teams, but to give fraud, AML, compliance, and member service teams the context they need to make better decisions while maintaining their respective responsibilities.
Year-After-Year,
the Industry’s Choice
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