Where conventional AML models stop at three stages — Placement, Layering, Integration — HTF™ maps five. This expanded framework captures the full operational arc of a criminal financial enterprise, from the first dollar earned to the infrastructure that keeps it running.
The first stage maps the illicit income streams that initiate the financial crime lifecycle. This includes the primary criminal activity — drug trafficking, cybercrime, fraud — and the mechanisms through which value is first extracted. HTF™ analysis at this stage identifies the revenue model of the criminal enterprise, not just the transactions it generates.
The second stage traces how illicit value first enters the financial system. HTF™ maps the organizational structure and actor network facilitating placement — not just the transactions themselves — enabling earlier detection at the point of entry.
The third stage detects asset movement across jurisdictions and instruments — the mechanisms through which criminal actors obscure the origin of funds while preserving and protecting accumulated value through real estate, commodities, securities, and other vehicles.
The fourth stage maps the mechanisms through which illicit value is converted into apparently legitimate form. HTF™ analysis identifies the specific conversion vehicles used and the actor networks that facilitate them — enabling earlier detection before the money fully disappears into the legitimate economy.
The fifth stage — unique to HTF™ — identifies the financial infrastructure that sustains ongoing criminal operations. This is the stage conventional AML doesn't see: the procurement of operational resources, the payment of criminal network personnel, and the reinvestment of proceeds into expanding criminal capacity. Detecting this stage enables proactive interdiction before the next revenue generation cycle begins.
Rather than replacing your existing detection infrastructure, TENet™,built on Hybrid Threat Central and powered by the HTF™ Taxonomy, acts as the intelligence layer that makes it dramatically more effective. TENet injects dynamic, human-intelligence-derived signals directly into your existing AML detection engines.
The result: your rules engines and ML models stop generating noise from patterns they were never trained to see and start producing case-quality alerts derived from threat signals grounded in how criminal enterprises actually operate.
Explore the Platform →By using the HTF™ investigation methodology and surfacing case-quality alerts, your team gains a clear understanding of the individuals involved and the nature of the potential crime — not just a transaction flag without context.
Through a structured, intelligence-led process and feedback loops, your FIU begins to see the true impact of its work — and builds an increasingly sophisticated picture of the threat networks operating in your institution's risk environment.
Detect trafficking by linking payment patterns, recruitment activity, and travel data through HTF™ behavioral typologies.
Trace revenue generation through obfuscation and storage to identify the full financial infrastructure of trafficking organizations.
Surface the organizational networks behind sanctions evasion — shell companies, front entities, and their beneficial owners.
Identify state-sponsored laundering, kleptocracy networks, and adversarial nations weaponizing financial infrastructure.
A 30-minute demo will show you how the HTF™ methodology translates into detection intelligence — and what it would produce against your alert queue.
