Global Financial Institution – Building an AML Investigations Platform to Support Federal Reporting

Introduction

A major financial institution needed to strengthen its anti–money laundering (AML) operations by creating a centralized platform to support deep-dive investigations and mandatory reporting to federal regulators. With tens of thousands of accounts requiring detailed analysis, the organization needed a scalable way for analysts to document findings, evaluate suspicious activity, and uncover linkages between accounts and potentially sanctioned or blacklisted entities.

‍

The Problem (Gut-Based Decisions)

Before the engagement, the AML investigations team faced significant constraints:

• More than 50,000 accounts required investigation-level review to comply with federal oversight.
• Analysts conducted research manually and stored findings in fragmented spreadsheets, emails, and shared folders.
• There was no unified system to track analyst work, aggregate findings, or trace conclusions back to source data.
• Identifying relationships between accounts, account holders, counterparties, and blacklisted entities was extremely difficult.
• Reports for the Federal Reserve required consistency, auditability, and documentation — attributes missing from the existing workflow.

With over 50 analysts working in parallel, the lack of a structured investigative system introduced operational, compliance, and regulatory risk.

‍

‍

The Solution (How Data Changes the Game)

We built a secure, scalable AML investigation platform that centralized all research activity and enabled deeper analysis, stronger reporting, and consistent regulatory compliance.

1. SQL Server Investigation Database

• Created a robust SQL Server–based repository to store all account research, analyst findings, risk assessments, and supporting evidence.
• Designed the data model to capture:
  • Account attributes
  • Transaction patterns
  • Analyst annotations
  • Sanctions and blacklist checks
  • Outcome classifications (e.g., suspicious, cleared, further review needed)
• Ensured auditability for regulators and internal compliance teams.

2. Analyst Workflow Integration

• Built a structured process for 50+ AML analysts to log findings consistently.
• Standardized how research was captured, reviewed, and approved.
• Eliminated fragmented spreadsheets and manual methods, improving quality and reducing duplication of effort.

3. Link Analysis & Entity Relationship Mapping

• Enabled analysts to identify connections between:
  • Accounts
  • Account holders
  • Known or suspected illicit entities
  • Blacklisted organizations
  • Related transactions
• Consolidated signals that previously existed across disparate systems, significantly improving investigative depth.

4. Tableau Reporting Layer

• Developed dashboards to support:
  • Investigator productivity and throughput
  • Case status and resolution across 50,000 accounts
  • Suspicious activity trends
  • Linkage visualizations between accounts and entities
  • Regulatory reporting summaries
• Provided compliance teams and executives with transparent, consistent insights.

5. Regulatory Support

• Ensured that all findings could be exported and consolidated into the required Federal Reserve AML reports.
• Delivered a system with end-to-end traceability — from raw data to analyst judgment to final report.

‍

Real-World Example (Specific Client Outcomes)

After implementation:

• The institution gained a single source of truth for AML investigative work.
• Analysts’ research became structured, searchable, and fully auditable.
• Linkages across accounts and high-risk entities were surfaced automatically, improving detection quality.
• The compliance team could generate regulator-ready reports with consistency and confidence.
• Investigation cycles became significantly faster and more accurate due to standardized workflows.
• Executive leadership gained visibility into AML operations, caseloads, and emerging risks.

The platform became essential for meeting federal reporting requirements and reducing compliance risk.

‍

Conclusion

By consolidating AML investigative data into SQL Server and enabling deep-dive reporting through Tableau, the institution transformed its ability to detect suspicious activity, perform consistent investigations, and report to the Federal Reserve with full confidence. The new platform standardized work across 50+ analysts, improved risk identification, and provided the transparency necessary for regulatory oversight — turning a manual, fragmented process into a controlled and efficient enterprise capability.