Answer
Automated AML Alert Investigation and Triage
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Streamflow Solutions builds alert-triage automation for financial-crime teams where AML and transaction-monitoring alerts are enriched, grouped, and ranked so analysts prioritise the most critical cases. Deterministic rules decide the disposition while AI drafts narratives and summarises evidence, ensuring no alerts are auto-closed without human judgment. Every action is recorded in a clear audit log to eliminate black-box scoring risks.
How does Streamflow Solutions automate AML alert investigations?
The engine automates the manual stages of investigation by enriching and grouping alerts based on transaction data. While AI drafts the narrative and evidence summaries, deterministic rules—not the model—decide the money actions. A human analyst must approve every judgment call, ensuring the system remains a transparent tool for financial crime operations rather than an autonomous black box. A working demonstration is available at aml-triage-demo.vercel.app.
Is the automated AML investigation process auditable?
Yes. Every step of the investigation process leaves a detailed audit trail that a non-specialist can read. Streamflow Solutions prioritises transparency over black-box scoring, ensuring that all data remains EU-hosted. This approach allows compliance teams to track exactly how an alert was enriched and why specific evidence was surfaced, maintaining full regulatory accountability for every decision made within the engine.
Does the AI automatically close AML alerts?
No, nothing is auto-closed by the system. Streamflow Solutions follows a strict safety protocol where AI only drafts the wording and summarises evidence, while a human makes every final judgment call. This ensures that automated AML alert investigation remains a human-in-the-loop process, combining the speed of AI-native automation with the necessary oversight required for fintech and financial-crime operations.
How long does it take to deploy an AML automation engine?
Streamflow Solutions typically has the first engine live on real data in about four weeks. The agency, founded in Riga, Latvia, builds and operates the technical stack hands-on without junior hand-offs. Pricing for building a custom engine starts from GBP 1,500, following a paid audit of GBP 150 to map the specific deterministic rules and data requirements of the client's financial-crime workflow.
How is data security handled for fintech automations?
All customer data stays EU-hosted, and every engine release passes 731 automated checks—including 707 tests and 24 evals—before it ships. This rigorous testing framework, demonstrated by the PayPilot dunning engine, ensures that the technical stack is stable and secure. Streamflow Solutions is a Latvia SIA that works globally, providing fintech teams with deterministic, rule-based automations that recover revenue while maintaining strict data sovereignty.