Where you are right now
Suspicious Transaction Pattern Detection
We build ML models on top of your existing transaction data to identify suspicious patterns your AML monitoring system may have missed.
Detect unidentified patterns
No changes to your current systems
Pre-Audit Gap Analysis
We analyze your data before FINTRAC does, surfacing suspicious transactions so you can review, document, and act before an audit finding becomes a fine.
Identify more suspicious transactions
Reduce your regulatory exposure
Why Us?
40x
Higher fines
FINTRAC's maximum penalties increased 40 times under Bill C-12, passed in 2026.
$176M+
Upto $176M+ in FINES
The largest penalty ever imposed on a single MSB, for unreported suspicious transactions.
BEFORE
NOT AFTER
The only time to fix compliance gaps is before FINTRAC audits your data, not after.
Who We Are
At Loblaws, I built AI-driven compliance programs that helped the organization navigate a Ministry of Health audit and avoid over $2M in potential fines. In 2025, I left my full-time role to launch my own independent practice, and have been delivering impactful projects for clients in the financial industry ever since.
Most recently, I've been working with RBC's Internal Audit team, building automation solutions across AML and regulatory reporting workflows.
With over 15 years of experience in quantitative research and data science, I've built and led teams at the intersection of finance and technology.
As the founding Data Science Director of a fintech startup that went on to a successful exit, I've seen firsthand what it takes to turn early-stage ideas into production-grade systems that drive real business outcomes.
