AI-Assisted Transaction Monitoring in 2026: What FINTRAC Will Expect From MSBs and FinTechs

Canadian regulators are becoming sharper and more data-driven in how they evaluate compliance programs. For MSBs and fintechs, that means AI tools used in transaction monitoring are now fair game for scrutiny, and not just in terms of what they do, but how they’re designed, governed, and reviewed.

A dark navy compliance-style background displays a dense, branching AI decision tree. The left side features blue geometric nodes and data pathways, gradually transitioning into orange as risk increases. The structure becomes more concentrated toward the right, culminating in a bright orange highlighted node representing a key risk decision point. Subtle ledger-grid patterns and faint directional data lines appear in the background, enhancing the technical and regulatory theme.

With FINTRAC expanding its definition of suspicious activity to include sanctions evasion and the FATF emphasizing AI governance and effectiveness, we are witnessing the beginning of a supervisory shift that compliance teams cannot afford to ignore.

Today we break down what FINTRAC will likely expect from Canadian reporting entities using automated or AI-supported monitoring in 2026 and how to get ahead of those expectations now.

Rising Priority: AI, Sanctions Evasion, and Performance Expectations

Filing STRs is a legal obligation. Filing useful ones, on time, and with the right context is becoming the new standard. Since 2024, that includes reports on transactions suspected of violating Canadian sanctions. These cases often involve cross-border transfers, new typologies, or obfuscated fund flows; patterns that legacy rule sets may not flag on their own.

At the same time, FINTRAC is deploying AI internally to sort through growing STR volumes. Their investment in digital supervision is a signal that they expect the private sector to use technology responsibly and be able to explain its outputs.

With Canada’s FATF mutual evaluation approaching, regulators will also be under pressure to demonstrate that the financial system can detect and respond to high-risk activity. That puts monitoring performance, especially for AI-enabled platforms, squarely on the agenda for 2026.

What FINTRAC Already Requires (Applies to Everyone)

The rules haven’t changed, but how they’re interpreted in exams has. Under the PCMLTFA, reporting entities must maintain a compliance program that includes:

A named compliance officer with clear responsibility
A documented risk assessment and written compliance program
Ongoing monitoring (not just reactive reporting)
Ongoing Training
A biennial effectiveness review / audit

If your AI tool helps you monitor transactions, it becomes part of the compliance program and must be tested, reviewed, and documented accordingly.

Where Expectations Are Headed (What to Prepare for in 2026)

Even without AI-specific rules, the following themes are already showing up in examinations and sector guidance. Expect them to be standard by 2026.

1. Transparency and Explainability

Be ready to walk through how your system identifies risk. FINTRAC doesn’t require technical detail, but they’ll expect plain-language descriptions of alert logic, scoring thresholds, and risk indicators used.

2. Validation and Testing

Effectiveness reviews are legally required. If your monitoring system includes AI, it must be part of that scope. Examiners may ask for evidence that you:

Tune thresholds based on actual transaction behaviour
Monitor alert-to-STR conversion rates
Evaluate false positives and coverage gaps

3. Governance and Accountability

Tools don’t govern themselves. Expect questions about who owns tuning decisions, who reviews model updates, and how those responsibilities are assigned within the organization.

4. Data Lineage and Integrity

If your system uses transaction history or customer data to generate scores, keep clear records of data flows, input fields, and version changes. That’s already required for STR defensibility.

5. Analyst Review

Even with automation, human judgment is still required. Your AI can assist, but not replace the analyst responsible for determining whether a transaction meets the threshold for suspicion.

6. Coverage of Risk Scenarios

Regulators may want to know if your system can flag:

Structuring across multiple small EFTs
Funds moving through intermediaries tied to sanctioned jurisdictions
Spikes in new customer transactions with limited KYC history

What’s Optional vs. What’s Now Expected

Feature / Practice	2025 Status	2026 Expectation	Comment
AI-based monitoring	Optional	Increasingly common	No legal mandate, but fast becoming best practice
Documented model governance	Best practice	Expected	CAMLO responsibility applies to models too
Explainability of alerts	Advised	Mandatory for audits	Needed to defend STR thresholds and triggers
Data lineage documentation	Rare	Necessary	Auditors will likely request input-output traceability
Effectiveness review of AI tools	Uncommon	Must be included in testing	Falls under existing review requirement

Bottom Line

By 2026, FINTRAC examiners will be less concerned with what software you're using and more interested in whether it’s producing useful results. If AI is part of your AML program, it must:

Generate alerts that reflect your actual risk profile
Be explainable to a non-technical examiner
Fall within your effectiveness testing cycle
Document how decisions are made and who’s accountable

MSBs and fintechs using automation should ensure their oversight keeps pace with their tools. Get this right, and AI becomes a compliance enabler, not an exam liability.

11.12.25

Written by Haik Kazarian, Head of Business Development

Reviewed by Tigran Rostomyan, Compliance Expert