Financial Services · Case study

Real-Time AML Detection: 75% Fewer False Positives, Zero Violations

A financial services firm cut false positives by 75%, scaled to 10x transaction volume, and passed its next regulatory exam with zero violations after we rebuilt its anti-money-laundering detection.

10× transaction volume handled
75% fewer false positives
Zero compliance violations
faster SAR preparation
The challenge

What they were up against.

The firm's existing AML system had been built for a transaction volume that was now a fraction of current levels — volumes had grown 10× in five years. Detection rules tuned for a different era generated false-positive rates exceeding 90%, meaning analysts spent almost all their time ruling out alerts rather than investigating real risk. Meanwhile, the system missed transaction patterns that didn't match its rigid rule set but were clearly suspicious to any trained analyst. The firm needed a system that could handle current and projected volume, cut false positives to a manageable level, and raise the quality of the alerts it surfaced.

  • Transaction volume had grown 10× — the legacy engine couldn't keep up
  • False-positive rates exceeded 90%, burying analysts
  • Real, suspicious patterns slipped through a rigid rule set
  • Analysts spent their time clearing noise, not investigating risk
The outcome

What changed.

False-positive rates dropped 75% in the first 90 days. Analysts who had been buried under an unworkable alert queue were now managing a prioritized list of genuinely suspicious cases. SAR filing time fell sharply. And when the firm's next regulatory examination reviewed the system, it found zero compliance violations — the first time in three examination cycles. Delivered as a Value Sprint and run through AI Office.

What we built

The system.

Hybrid detection engine

Rule-based detection — updated and tuned for the firm's current risk profile — combined with machine-learning models trained on historical SAR data to catch patterns the rules would miss while cutting false-positive noise.

Near-real-time processing

Transactions scored as they happen, with alerts prioritized by risk score so the highest-risk cases surface first.

Analyst investigation summaries

Alerts arrive with pre-populated investigation summaries that cut SAR preparation time by 75%.

Horizontally scalable architecture

Built to scale out with volume — so it won't be outgrown again.

What we shipped

Inside the build.

Real-Time AML Detection: 75% Fewer False Positives, Zero Violations — product screens
You guys really exceeded my expectations. The understanding the team has of our complex business is impressive. We’ve come a long way and you guys made it happen.
— Omer Khan, Senior Director of Technology, K2 Integrity
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