Sanctions Routing Audit Engine

2.60

Derivation Chain

Step 1 U.S.–Iran nuclear negotiation tensions

→

Step 2 Export companies' sanctions risk management demand

→

Step 3 Sanctions evasion payment pattern detection

→

Step 4 Payment routing audit service for bank compliance teams

Problem

Compliance teams (3–10 staff) at small and mid-sized Korean banks and savings banks need to detect payments routed through sanctioned countries (Iran, North Korea, etc.) in SWIFT transactions. Existing AML systems only flag direct transactions, missing indirect routing patterns through third countries. Failure to detect these can trigger U.S. OFAC sanctions that block the bank's entire dollar clearing capability, so staff spend 15 hours per person per week on manual review.

Solution

Upload SWIFT MT messages (103/202) to visualize payment routing as a graph and automatically detect sanctioned-country transit patterns (intermediate correspondent banks, abnormal split transactions, etc.) using a hybrid rule + ML engine. Ranks suspicious transactions by risk level for prioritized review. Auto-generates draft SARs (Suspicious Activity Reports) for regulatory filing.

Target: Compliance teams and AML officers at small and mid-sized banks and savings banks with assets of $750M–$7.5B

Revenue Model: SaaS Monthly Subscription at ~$740/institution, including 100K transactions/month, ~$0.004 per excess transaction

Ecosystem Role: Regulation

MVP Estimate: 1_month

NUMR-V Scores

N Novelty

4.0/5

U Urgency

4.0/5

M Market

2.0/5

R Realizability

1.0/5

V Validation

3.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (54%)

Tech Complexity

19.3/40

Data Availability

23.1/25

MVP Timeline

12.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (52/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

3.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [high] AI/ML [medium] Frontend [medium]

Dashboard