A Framework by Nic McKinley · Former CIA Officer · Founder of DeliverFund
The Disruption Probability Model
A compound-probability framework that turns intelligence tradecraft into math — collapsing a trafficker's 90% success rate to under 3% by disrupting all ten points of their operation at once.
Definition
What the Disruption Probability Model is.
The Disruption Probability Model is a compound-probability framework for dismantling human trafficking networks. It treats every trafficking operation as a chain of independent transactions that must all succeed, then calculates how the trafficker’s odds collapse when private-sector partners disrupt each link at the same time.
Developed by former CIA officer and DeliverFund founder Nic McKinley, the model adapts counterterrorism network-disruption methodology to civilian criminal enterprise. Rather than relying on a single point of enforcement, it engages telecom, social media, financial, transportation, and hospitality partners across ten sequential points of disruption.
The core insight is mathematical: because the disruption events are independent, their effects multiply. A trafficker who succeeds 90% of the time under single-point enforcement succeeds less than 3% of the time once a modest disruption probability is applied at all ten points.
The Math
How the odds collapse.
Each trafficking operation must complete ten sequential transactions. When an independent disruption probability is applied at every point, the compound probability of complete success falls rapidly — at a fraction of the cost of reactive enforcement.
| Scenario | Disruption per point | Trafficker success rate | Operations disrupted |
|---|---|---|---|
| Status quo (no intervention) | — | 90% | Baseline |
| Modest disruption | 20% per point | 10.7% | 89.3% disrupted |
| Moderate disruption | 30% per point | 2.8% | 97.2% disrupted |
| Varied real-world | mixed rates | 1.2% | 98.8% disrupted |
A 30% disruption rate at each of ten points leaves only a 2.8% chance of trafficker success. Each added point also forces traffickers to spend more on new infrastructure, compressing their margins — and removing high-centrality nodes collapses coordination across the entire network.
Methodology
How the model is applied.
- 01
Map the transaction chain
Every trafficking operation is decomposed into the ten sequential transactions it must complete — from recruitment and advertisement to transport, service provision, payment, and banking. Each becomes a measurable point of disruption.
- 02
Assign a disruption probability to each point
Drawing on intelligence tradecraft and real operational data, each point is assigned an independent disruption probability (dᵢ) — the likelihood that a cross-sector partner detects or interrupts that link.
- 03
Apply compound probability
Because the disruption events are independent, their effects multiply: P(success) = ∏(1 − dᵢ). The trafficker's probability of completing every transaction collapses exponentially as points are added.
- 04
Engage cross-sector partners simultaneously
Telecom, social media, financial, transportation, and hospitality partners act at their respective points at the same time. With no single avenue to squeeze toward, every trafficker adaptation forces new infrastructure and new friction.
- 05
Measure cumulative disruption and compress margins
Disruption is tracked across the full chain rather than at a single gate. The result is documented in the field — from 21 trafficking rings uncovered through financial partners to 94% machine-learning accuracy identifying trafficking advertisements.
Disruption Probability Model
Questions, answered.
- What is the Disruption Probability Model?
- The Disruption Probability Model is a compound-probability framework, developed by former CIA officer and DeliverFund founder Nic McKinley, for dismantling human trafficking networks. It treats each trafficking operation as a chain of ten independent transactions that must all succeed, then calculates how the trafficker's odds collapse when private-sector partners disrupt every link simultaneously.
- How does the compound probability model work?
- Each trafficking operation must complete ten sequential transactions, and each has an independent disruption probability. Because the disruption events are independent, their effects multiply — P(success) = ∏(1 − dᵢ). At a 30% disruption rate per point the trafficker failure rate reaches 97.2%; even a modest 20% per point yields 89.3% cumulative disruption.
- Why is disrupting all ten points more effective than single-point enforcement?
- Single-point enforcement disrupts fewer than 10% of trafficking operations and is easy to adapt around — criminals simply route past one hurdle. Disrupting all ten points simultaneously leaves no single avenue to squeeze toward, so every adaptation forces new infrastructure and new friction while the compound probability of success falls below 3%.
- What are the ten points of disruption?
- They are the ten sequential transactions every trafficking operation must complete: market opportunity (telecom & tech), recruitment (social media), control, advertisement (online platforms), communication, transport (transportation & hospitality), service provision (hospitality & rentals), payment (financial institutions), banking, and legal compliance. Each maps to an industry that can act as a disruption partner.
- Has the Disruption Probability Model produced real results?
- Yes. The multi-sector approach has documented results: 21 trafficking rings uncovered through a single bank's financial infrastructure, 94% machine-learning accuracy identifying trafficking-associated advertisements, and a measurable drop in recruitment within 30 days of the Backpage shutdown.
- Who created the Disruption Probability Model?
- Nic McKinley — a former CIA officer, U.S. Air Force Pararescueman with 30 combat deployments, Harvard graduate, and founder of DeliverFund — developed the model by adapting counterterrorism network-disruption methodology to civilian criminal enterprise.
Point of Disruption
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