In the world of financial services, access has long been a barrier. While artificial intelligence is revolutionizing the speed and efficiency of money management, its greatest potential may lie elsewhere: in expanding who gets to participate.
When designed intentionally, technology can turn complexity into clarity. Across North America, inclusive fintech platforms are helping immigrants, women, and financial beginners decode their money habits, plug financial leaks, and create personalized investment plans—often for the first time.
This article explores how inclusive AI is transforming access to financial empowerment, and what it means for the future of fintech.
The problem: Finance has a gatekeeping problem
Traditional financial systems weren’t built for everyone. They assume a level of language fluency, institutional trust, and financial literacy that many newcomers simply don’t have. Research from Prosper Canada shows that 34–46% of newcomers to Canada experience financial vulnerability, often due to lack of familiarity with financial systems and products.
This creates exclusion at every level. From paperwork-heavy bank applications to advice steeped in jargon, even opening a TFSA or understanding retirement planning can feel intimidating. Statistics Canada also found that newly arrived immigrant families are far more likely to be “credit invisible” than Canadian-born citizens (Statistics Canada, 2023).
Analysis of first-time investor behaviour confirms what many in financial inclusion circles already suspect: most aren’t starting from zero—they’re starting from behind.
The opportunity: AI is not an optimizer, but an on-ramp
Most headlines around AI in finance focus on automation, fraud detection, or high-frequency trading. But there’s a more human-centered use case: access.
AI tools can do more than crunch numbers—they can translate. These tools convert fragmented financial behaviour into digestible, actionable insights. In under 15 minutes, users can:
- Calculate their net worth across multiple accounts
- Detect “money leaks” (small recurring expenses that drain savings)
- Identify their investor profile and risk comfort
- Generate a personalized investment roadmap, including asset allocation and financial goals
All without needing to speak to an advisor, read financial whitepapers, or guess what’s “normal.” These types of AI applications demonstrate what the World Economic Forum calls the “democratizing potential” of machine learning in financial services (WEF, 2025).
What we’ve learned: Better design is a product of data and empathy
AI alone isn’t the magic. The real power is in combining machine intelligence with cultural awareness. Insights from user behaviour reveal what new wealth builders really need:
- Simplicity without condescension
- Contextual tips that reflect immigrant realities (e.g., remittances, cash jobs, or unregistered savings)
- Emotional reassurance: many users carry shame or fear around money
This behavioural feedback loop helps train better AI models. These systems learn not just from numbers, but from confusion points, skipped questions, and repeat behavior. They adapt to user emotion, not just transaction volume. TD’s 2018 Responsible AI survey noted a similar demand: Canadians want financial AI that is personalized, humanized, and bias-aware (TD Bank, 2018).
The result is that you get tools that feel less like a coach and more of a calculator.
Implications: Inclusive AI is a strategic advantage
Fintechs that prioritize accessibility will have a competitive edge. As global migration increases, financial institutions can no longer afford to ignore the needs of first-time investors. Windmill Microlending describes economic inclusion as both a social mission and a market opportunity (Windmill Microlending, 2022).
Designing AI for this audience doesn’t just meet a social need—it unlocks a vast market of eager learners. These are people who don’t want charity…rather, they are looking for guidance, clarity, and dignity.
And when they get it? They don’t just invest money. They invest trust.
Looking ahead: Putting people first is the cornerstone of the future of AI
The next generation of AI tools must be multilingual, emotionally intelligent, and bias-aware. They must reflect the messy realities of real users—not just the ideal profiles of legacy institutions.
More than optimization, AI’s greatest promise in finance is inclusion. It’s not about making rich people richer, faster. It’s about giving everyone the tools to grow.
