|  CASE STUDY · AML · TIER 2 ESCALATION

How a financial crime desk stops briefing regulators with screenshots

A major financial institution assembles AML escalation packs across siloed systems; KnowledgeHub sits above them as a semantic layer with citation-first retrieval and human-approved drafts.

Every assertion carries its source.

|  The problem

What fails is the assembly

The evidence exists. Finding it and proving it, is the problem.

An AML escalation desk at a major Nordic financial institution has a process that works until it doesn't. Tier 2 reviewers are skilled. The alert logic is sound. The risk typologies are well understood.

01

Lineage on every passage

Each assertion is tied to its corpus fragment, ontology release and timestamp.

02

Drafts, approved by analysts

Bounded agents assemble cited drafts. Analysts approve before anything crosses the perimeter.

03

Graphs instead of screenshots

Escalations are rehearsed with reproducible retrieval graphs instead of screenshot-led decks.

|  Inside the analyst's day

From alert to pack, with the trail intact

01 · Escalation

The alert is escalated

A tier 2 alert lands on the desk. The retrieval starts before the analyst opens it.

KnowledgeHub traverses the knowledge graph: entity relationships, transaction patterns, prior SAR filings, sanctions exposure and CRM notes.

Transaction monitoring
02 · Retrieval

The evidence, ranked and attributed

The result is a ranked set of cited passages.

Each passage is tagged with its source document, ingestion timestamp and the ontology version that classified it.

Knowledge graph
03 · Review

Evaluate, correct, approve

The analyst's job is not to find the evidence. It is already surfaced.

The analyst evaluates it, corrects it where needed and signs off. Nothing leaves the desk without that approval.

Case management
04 · Months later

Same query, same result

The pack that leaves the desk carries every citation intact.

The supervisor sees the data trail behind the narrative, and compliance can reproduce the retrieval graph months later with the same ontology version.

Retrieval graph
|  What changed

Provenance, not recollection

|  Hero metric
72%

Estimated reduction in manual citation assembly time.

  • Supervisors review packs rather than reconstruct them.
  • Cross-team handoffs carry a cited narrative instead of a note saying "see attachments".
  • Compliance has a reproducible record of every retrieval, tied to an ontology release.
  • An examiner's question is answered with a citation chain.
Sector
Financial sector
Region
Denmark / Nordics
Org scale
1k–15k relevant seats
Personas
Tier 2 AML reviewers, supervisors, financial crime compliance, IT security
Products
KnowledgeHub · Case workspace · Graph traversal · Agents
Compliance
GDPR-aligned processing · ISO 27001 posture · configurable retention
|  Outcomes

Operational outcomes

Estimated cross-team referrals with lineage
621

per quarter

Estimated time to first cited narrative
113

days

Estimated documents reconciled per reviewer hour
824

files

|  Use cases

More from Financial institutions

|  Next step

Easy to start. Safe to stop.

The pilot runs at a fixed price: we map the workflow, deploy it in your environment and prove it on your own cases. Then you decide.

Fixed price · Fixed timeframe

  1. 01

    Map the workflow

    Two weeks with your people where we document what happens today, including the parts nobody wrote down.

  2. 02

    Deploy in your environment

    Inside your tenancy, on your data residency terms, with no exports and nothing leaving through the side door.

  3. 03

    Prove it under audit

    Controlled evaluation against your own cases with compliance and the process owner signing off before go-live.

  4. 04

    Run in production

    We stay on with retraining, reporting and ongoing oversight for as long as the workflow runs.

Fixed price, Fixed timeframe. 8–12 weeks pilot: Continue (Expand once you know it works) / Stop.