The Robots Are Good With Money

Picture this: quiet boardrooms across Canada suddenly buzzing as artificial intelligence (AI) moves from buzzword to balance sheet. Finance teams at RBC, TD, BMO, and countless SMBs aren’t just testing AI, they’re transforming operations with it. From automating back-office workflows to delivering personalized investment insights, AI is reshaping the DNA of Canadian finance.

This isn’t futuristic hype. It’s happening now, across Edmonton, Toronto, Montreal, Vancouver, and beyond.

Canada’s Finance Sector: A Global AI Leader

According to a KPMG survey of 2,900 firms across 23 countries, 82% of Canadian organizations are already using or piloting AI in finance, well above the 71% global average. Even better, 69% report ROI that meets or exceeds expectations.

Canadian firms aren’t just embracing AI, they’re doing it strategically. The result? Smarter decisions, more agility, and a competitive edge.

Key Use Cases: From Automation to Advisory

1. Risk Management amp; Fraud Detection

AI is revolutionizing risk. Machine learning now flags suspicious transactions in real time, helping analysts focus on complex cases. One major Canadian bank cut fraud losses significantly using such tools.

For credit risk, deep learning models improve borrower evaluation, spot early warning signs, and reduce loan defaults. And with FINTRAC preparing to deploy AI-powered AML scorecards in 2026, automated compliance is set to become the norm.

2. Customer Service amp; Personalization

Meet NOMI, RBC’s AI-powered finance assistant. It analyzes spending, sets budgets, and has helped users save over C$1.5 billion. Its chatbot, Ask NOMI, provides quick answers in-app, helping millions engage more actively with their finances.

At Scotiabank, chatbots handle 40% of customer inquiries with nearly 90% accuracy. ATB Financial Financial uses a conversational AI chatbot that now handles two-thirds of common questions, pushing satisfaction over 90%.

Meanwhile, TD Bank is piloting large language model (LLM) tools in contact centres and using GitHub Copilot to boost developer productivity by 20+ hours every two weeks.

3. Investment, Trading amp; Wealth Management

AI is transforming capital markets and wealth advisory:

• Conquest, based in Winnipeg, raised C$110 million in 2025 for its AI-driven financial planning platform used by thousands of  advisors across institutions like RBC and Wealthsimple.

• Overbond uses neural networks to predict bond pricing and issuance timing, reducing costs and improving transparency for 80+ Canadian bond issuers.

• RBC’s Aiden platform powers electronic trading with machine learning, part of a broader AI strategy aimed at C$1 billion in returns.

4. Back-Office & Financial Automation

AI’s biggest impact may be behind the scenes:

• RPA (Robotic Process Automation) handles repetitive tasks like invoice processing and reconciliation, reducing errors and freeing teams for strategic work.

• Microsoft Copilot for Finance is helping mid-sized Canadian firms streamline forecasting and reporting.

• AI tools can read unstructured accounting documents, flag anomalies, and enable real-time auditing.

• Montreal-based Fundica connects startups and SMEs to relevant funding programs through an AI-driven matchmaking platform.

Infrastructure: Research, Regulation amp; Responsibility

Canada’s rise in AI is no accident. The Pan‑Canadian AI Strategy invested $600M+ into institutes like Mila - Quebec Artificial Intelligence Institute (Montreal), Vector Institute (Toronto), and Amii (Alberta Machine Intelligence Institute) (Alberta), fueling R&D and industry partnerships.

Major banks built internal capabilities. RBC’s Borealis AI, launched in 2016, supports tools like NOMI and Aiden through a private AI cloud that spans four cities.

On the regulatory side, initiatives like Bill C‑27 (Digital Charter), the Artificial Intelligence and Data Act, and the new Canadian Artificial Intelligence Safety Institute (CAISI) are ensuring AI in finance remains safe, ethical, and transparent.

The Challenges: Risk, Bias & Stability

As adoption grows, so do the challenges:

• Explainability & Bias: AI models used in lending or risk assessments must be transparent. Deep learning models can be “black boxes,” making it critical to justify decisions and minimize bias.

• Systemic Risk: Overreliance on similar AI models across institutions may amplify economic shocks, raising concerns for financial stability.

• Inflation Volatility: The Bank of Canada Bank of Canada warns AI-fueled price optimization could contribute to volatile inflation, complicating monetary policy.

• Compliance Pressure: With real-time monitoring expected from regulators, banks must invest in AI that supports explainability, traceability, and compliance by design.

Case Studies: AI in Action

RBC

• Scaled NOMI and Aiden with support from Borealis AI.

• Built in-house AI infrastructure and digital innovation teams.

• Targets C$1 billion in AI-driven returns.

ATB Financial

• Finn AI chatbot handles 65% of inquiries with 90%+ satisfaction.

• Automated 200+ back-office processes using NLP and RPA.

• AI-based recommendations now reach 240,000+ clients per year.

TD Bank

• Gen-AI tools reduce wait times and accelerate development cycles.

• Pilot programs blend human workflows with LLM-powered systems.

Scotiabank & BMO

• Scotiabank’s chatbots and fraud detection systems improve service and security.

• BMO focuses on Gen Z clients using personalized insights and AI-driven analytics.

Conquest & Overbond

• Conquest empowers advisors with personalized, AI-powered planning.

• Overbond drives efficiency in fixed-income markets through predictive analytics.

What’s Next: The Future of AI-Powered Finance in Canada

Mid-Market Expansion AI adoption is growing across Canadian SMEs. Over 80% of mid-sized firms are piloting AI in finance. Expect widespread use in tax, treasury, audit, and decision support as tools become more accessible.

Smarter LLM Tools Generative AI is finding new roles in policy summarization, document review, and internal reporting. Customer-facing use is coming, but must balance innovation with ethical safeguards.

Stronger Regulation & Ethical AI New rules will require fairness, explainability, and auditability, especially in high-stakes decisions like credit scoring. CAISI and related laws aim to guide institutions toward responsible deployment.

AI Talent Pipeline Banks like CIBC are hiring hundreds of AI and data professionals. At the same time, Canadian universities are adapting curricula to support this transformation.

Transforming Finance, Responsibly

AI in finance is no longer a promise, it’s progress. It’s reducing fraud, improving service, sharpening investment decisions, and driving productivity. But it’s also doing something bigger: humanizing finance.

By taking over repetitive tasks, AI lets employees focus on strategy and creativity. It helps advisors personalize client interactions. And with strong ethics and smart regulation, Canada is shaping a financial system that’s not just intelligent, but fair and inclusive.

For finance leaders, from bank execs to SMB CFOs, the message is clear: invest in AI not just to automate, but to elevate.

Because in Canada today, AI isn’t just powering finance. It’s transforming it, for good.

Ready to talk FinTech with Bevertec? Contact us today to discover how we can help you transform your banking services.