AML Risk Intelligence Platform — Strategic Analysis

📊 Problem Validation

✅

Is this a real pain point?
Absolutely yes. This is an operational crisis, not a theoretical problem.

90-95%

False positive rate

30-45 min

Per alert investigation

$50-60B

Annual AML spend

$3-4B

AML software market

The "Plausibility Gap"

        Traditional systems flag patterns but can't answer: "Does this $2M invoice for 'consulting services' make sense given this 3-person company?"
      

Investigators currently:

Google companies manually
Eyeball invoices for inconsistencies
Make judgment calls with incomplete context
Document inconsistently across team members

⏰ Why Now?

1. LLMs Changed What's Possible

Document understanding at scale is now feasible. Entity extraction, summarization, inconsistency detection — previously required expensive NLP teams. This product couldn't exist 3 years ago.

2. Regulatory Pressure Intensifying

AMLA (EU) creating centralized AML authority (2025-2026)
FinCEN beneficial ownership rules
"Effectiveness" is the new buzzword

3. Budget Scrutiny

Banks cutting costs, AML teams asked to "do more with less." AI investment getting greenlit where traditional software wouldn't.

Window: 18-24 months before incumbents have credible offerings.

💪 Solution Strengths

What's Strong

"Copilot, Not Autopilot" — Regulators will never accept black-box verdicts
Pre + Post Document — Full workflow coverage
Evidence Lineage — Every signal has citations
On-Premise Option — Non-negotiable for Tier 1

What's Missing

Integration strategy unclear
Feedback loop for learning
Entity data source strategy
TBML complexity (deep rabbit hole)
KYC integration

⚠️ Key Risks

Risk	Severity	Mitigation
Hallucination in high-stakes context	Critical	Strict citations, confidence thresholds, human-in-loop
Data privacy / model training	High	On-prem, no cross-client learning
Long sales cycles (banks)	High	Land with smaller FIs, build references
Incumbent bundling	Medium	Move fast, build workflow switching costs

🏆 Competitive Landscape

Company	Focus	Gap
Hummingbird	SAR filing automation	Weak on pre-decision
Quantifind	Entity resolution	Weak on documents
ComplyAdvantage	Screening/monitoring	Not investigation-focused
Napier AI	Alert triage	Not plausibility analysis
WorkFusion	Broader automation	Less focused

        Your differentiation: "Can this counterparty actually deliver what's described?" — Nobody owns this. This is your category-defining message.
      

🎯 Go-to-Market

Ideal First Customers

Regional US banks ($10-100B assets) — Sophisticated pain, faster procurement
European challengers — Tech-forward (Monzo, N26, Revolut)
Payment processors / fintechs — Growing AML pain

Sales Motion

60-90 day POC with specific use case (trade finance or high-value wires)
Prove 40%+ investigation time reduction
Expand to more alert types

Pricing

Per-seat: $2-5K/month/investigator
Per-alert: $5-15/alert

🔬 Validation Questions

What to Ask in First 10 Conversations

"Walk me through your last complex investigation"
"What % of alerts require document requests?"
"How do you verify a counterparty can actually deliver?"
"What would make you look like a hero to your boss?"
"What happened in your last regulatory exam?"

Signals to Watch

🟢 Strong: "We Google every company and it takes forever"

🟢 Strong: "Our false positive rate is killing us"

🟢 Strong: "We just failed an exam on documentation"

🔴 Weak: "We're happy with our current tools"

🔴 Weak: "AI makes me nervous for compliance"

📋 Summary

Factor	Assessment
Problem validity	✅ Acute, expensive
Market size	✅ $50B+ spend
Timing	✅ LLM unlock + regulatory
Solution-market fit	⚠️ Needs workflow validation
Competition	⚠️ Crowded, but angle is differentiated
Go-to-market	⚠️ Long sales cycles

🚀 Recommendations

Narrow initial use case — Trade finance TBML or correspondent banking
Build entity data partnerships early — Don't boil the ocean
Get a design partner — One bank willing to co-develop
Instrument everything — Prove ROI quantitatively