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截图

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细节

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Basmu 主要特点

• Narrative intelligence
  Produces investigation narratives and case conclusions that link findings to cited evidence.
• Graph / network analysis
  Builds transaction and entity networks to help investigators see pathways, clusters, and linked activity.
• Alert & case investigation
  Ingests alerts, STRs/referrals, and structured case data to support investigator workflows on top of existing monitoring systems.
• Closed-case miss discovery
  Re-examines closed cases to surface candidate missed patterns for analyst review (candidate-only; not auto-filed).
• Explainability & audit trail
  Provides explainable outputs and provenance so conclusions can be reviewed, supervised, and defended.
• Predicate-offence assessment
  Assesses possible predicate-offence angles with evidence grounding; surfaces candidates for human adjudication.
• Evidence retrieval & synthesis
  Pulls related transactions and case context into a structured evidence view to reduce manual gathering across fragmented sources.
• Entity & relationship discovery
  Identifies subjects, counterparties, and associates to surface connections relevant to the investigation.
• Hypothesis generation & testing
  Generates investigative hypotheses (including benign explanations), supports structured challenge, and helps analysts confirm or argue down alerts.
• Behavioral & transaction analysis
  Applies typology-oriented transaction analysis (e.g. structuring, layering, fan-in/out, concentration) to support investigative assessment.

Basmu 优势

• Defensible narratives
  Produces evidence-backed investigative narratives suitable for review and escalation.
• Faster investigations
  Reduces time spent gathering evidence and reconstructing activity across fragmented case data.
• Improved case coverage
  Helps teams work more alerts/cases with the same investigative depth.
• Fits existing TM stacks
  Complements transaction monitoring—monitoring flags activity; CADA helps investigate and explain it.
• Better connection discovery
  Surfaces entity and network links that are easy to miss in manual review.
• Lower investigator workload
  Automates repetitive retrieval, linking, and first-pass hypothesis work so analysts focus on judgment.
• Explainable decision support
  Keeps humans in control; outputs are for adjudication, not autonomous filing.
• Higher investigation quality
  Structures evidence, hypotheses, and conclusions for more consistent alert handling.
• Cross-institution flexibility
  Modules support banks, fintechs, FIUs, and related regulated users from structured case inputs.

谁应该使用 Basmu？

• Banks
  Deploy as an investigation layer above existing TM and core banking data.
• Fintechs
  Support risk-ops investigation of payment and account alerts under regulatory expectations.
• AML investigators
  Primary users investigating alerts and assembling evidence-backed case conclusions.
• Fraud investigators
  Investigate suspicious payment and account activity with entity/network context.
• Financial-crime compliance teams
  Manage alert investigation quality, consistency, and supervisory review.
• Regulated financial institutions
  Use modular investigation workflows without replacing existing monitoring stacks.
• Compliance officers / supervisors
  Review CADA outputs, evidence gaps, and investigator decisions with auditability.
• Financial intelligence units (FIUs)
  Enrich STRs/intelligence packages and support case assessment workflows.

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徽章

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Basmu 替代品

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使用的技术

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