Anti-money laundering
AML teams triage alerts, investigate cases, write reports and track typologies, under strict confidentiality.
The challenge
Section titled “The challenge”- Most alerts are false positives that look like earlier ones.
- Report narratives are written from scratch each time.
- Typology knowledge sits with a few experienced investigators.
Why SrvDB fits
Section titled “Why SrvDB fits”- Alert prioritisation by similarity to past dispositions.
- Typology matching of case narratives.
- Confidential by design: data stays on your infrastructure.
Five projects, five levels
Section titled “Five projects, five levels”Each project has its own page: the problem, how SrvDB powers it, what changes, architecture, use cases, core code and limits.
| Level | Project | What it does |
|---|---|---|
| 1 · Beginner | Typology Library | Search money-laundering typologies and red flags by description. |
| 2 · Intermediate | Alert Prioritizer | Ranks AML alerts by similarity to past true and false positives. |
| 3 · Advanced | Adverse Media Matcher | Deduplicates and matches adverse media to customers. |
| 4 · Expert | AML Investigation Agent | An investigator agent with memory across cases, typologies and media. |
| 5 · Frontier | Emerging Typology Radar | Detects clusters of cases far from every known typology. |