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Financial Crime Operations

Agentic KYC, AML, fraud, and sanctions casework with policy-bound investigation, human adjudication, and audit evidence.

Use Case PlaybookLast reviewed: Edit on GitHub
At a glance

Purpose

Help financial-crime teams move from alert queues to evidence-bound case decisions. ContextOS coordinates investigation agents that gather facts, compare policy, draft narratives, and recommend disposition while keeping final high-risk decisions with accountable humans.

Why this is agentic-first

KYC, AML, sanctions, and fraud workflows are not single prompts. They require multiple evidence sources, policy interpretation, identity resolution, adverse-media review, transaction analysis, case writing, and supervisory approval. McKinsey describes agentic AI in financial-crime contexts for client onboarding, KYC refreshes, transaction monitoring, sanctions, and fraud investigations from alert to case closure.

ContextOS is useful because every case must explain why the agent touched each source, which rule fired, who approved the disposition, and which evidence snapshot supports the decision.

Context Pack

LayerRequired entries
decision_layer.decision_specs[]fincrime.alert.triage, fincrime.kyc.refresh, fincrime.case.disposition, fincrime.report.file
policy_layer.policy_bundles[]AML policy, sanctions policy, fraud policy, customer risk policy, data-retention policy
policy_layer.approval_gates[]GATE_INVESTIGATOR_REVIEW, GATE_MLRO_APPROVAL, GATE_REGULATORY_REPORT
tooling_layer.adapter_registry[]adp_corebanking.lookup, adp_kyc.fetch, adp_txn.analyze, adp_sanctions.screen, adp_case.update, adp_report.file
memory_layer.write_classes_allowedcase_pattern, policy_correction, decision_outcome
evaluation_layer.eval_targets[]false-negative rate, escalation quality, case-narrative completeness, audit acceptance

Agent roles

AgentResponsibilityBoundary
Alert Triage AgentClusters alerts and resolves customer, account, and transaction identity.Cannot close cases.
Evidence AgentFetches KYC, sanctions, transaction, and adverse-media evidence.Read-only except case notes.
Policy AgentMaps evidence to policy rules and required case fields.Cannot override policy.
Narrative AgentDrafts case summary, rationale, and regulator-ready timeline.Draft only.
Supervisor AgentChecks completeness, contradictions, and approval requirements.Can block disposition.

Execution flow

  1. invokeAgent arrives with intent=fincrime.investigate, alert IDs, jurisdiction, customer ID, and queue priority.
  2. Compiler pins policy bundles, permitted data sources, jurisdiction overlays, retention limits, and case schema.
  3. Alert Triage Agent clusters duplicate or related alerts.
  4. Evidence Agent gathers account, KYC, transaction, sanctions, and adverse-media evidence.
  5. Policy Agent evaluates rule matches and required fields.
  6. Narrative Agent drafts a case package with citations and gaps.
  7. Supervisor Agent verifies evidence completeness and conflict status.
  8. Low-risk false positives can be recommended for human batch approval. Suspicious activity, sanctions hits, or regulatory filings require named approval.
  9. Tool Gateway updates case system or files report only after gate approval.
  10. ContextOS emits a DecisionRecord with decision_key="fincrime.case.disposition".

Decision gates

GateTriggerRequired evidence
GATE_INVESTIGATOR_REVIEWAny case closure, escalation, or customer risk-rating change.alert cluster, rule matches, evidence refs, narrative
GATE_MLRO_APPROVALSuspicious activity recommendation or high-risk jurisdiction.full case package, policy citations, reviewer notes
GATE_REGULATORY_REPORTFiling, correction, or withdrawal of regulated report.filing payload, jurisdiction rule, approval chain

Failure modes

  • Identity collision - CEID/SID resolution must prove the customer, account, and transaction belong to the same entity.
  • Source conflict - contradictory KYC or sanctions data triggers escalate instead of disposition.
  • Policy version mismatch - Compiler refuses packs that mix incompatible policy versions.
  • Narrative without evidence - Supervisor blocks case updates when claims lack evidence_refs.
  • Over-automation risk - high-risk decisions stay as recommendations until human approval.

Metrics

  • Case package completeness.
  • False-positive reduction with no increase in false negatives.
  • Investigator acceptance rate.
  • Time from alert to first decision.
  • Regulatory filing defect rate.
  • Number of policy gaps discovered through operator correction.

Research signals