Zero Regulatory Findings on the First AML Audit
A financial services firm consolidated 12 fragmented source systems into one audited AML data warehouse — and passed its first regulatory examination with zero findings.
What they were up against.
K2 Integrity's compliance team was running anti-money-laundering analysis across 12 separate source systems — each with its own data model, extract process, and interpretation of the same transaction types. Filing a Suspicious Activity Report meant analysts manually reconciling exports from multiple systems: days of work, with human error at every step. Regulators had already flagged the fragmentation in a prior exam — the firm couldn't demonstrate end-to-end transaction coverage, a baseline requirement for any credible AML program. The next examination was 18 months out, and the system had to be operational and demonstrable, not still in development.
- BSA/AML coverage — demonstrable, auditable coverage of every reportable transaction type across all business lines
- SAR deadlines — reports due within 30 days of detection; manual processes were consistently at or over the limit
- Examination risk — continued fragmentation risked Matters Requiring Attention or formal enforcement
- Operational drag — analysts spending 60% of their time on data reconciliation instead of investigation
How we did it.
Source-system inventory
Complete mapping of all 12 systems — data models, volumes, extract mechanisms, and coverage gaps. We documented everything before touching anything.
Unified data model
A normalized transaction model that accommodated every source type while preserving the audit trail SAR documentation requires.
ETL pipeline construction
Reliable, monitored pipelines from each source, with data-quality checks at every stage and alerting on any extraction failure.
AML analytics layer
The rule-based and statistical detection models the compliance team needed, plus dashboards for analyst workflow and SAR prep.
What changed.
When the examination arrived, the firm demonstrated end-to-end transaction coverage from every source system into a single, audited, documented warehouse. The examiners reviewed the architecture, the data-quality controls, and the detection-model documentation — and issued zero findings on the first try. Beyond compliance, it reset the team's operating model: SAR filing dropped from days to hours, and analyst time on data reconciliation fell from 60% to under 10% — freeing them to do the investigation work they were hired for. Delivered as a Value Sprint and run through AI Office.
The system.
Unified transaction data warehouse
All 12 source systems consolidated, normalized, validated — with a full audit trail.
12-source ETL pipeline suite
Per-source pipelines with data-quality monitoring, reconciliation checks, and failure alerting.
AML detection engine
Rule-based and statistical models for the firm's risk profile, configurable by compliance without engineering support.
Analyst workflow dashboard
Case management that surfaces flagged transactions, supports investigation, and produces SAR-ready documentation packages.
I can't say enough good things about your team. You 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.
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