Empower customers to reach financial goals
Overview
BMO Insights is a free feature in the BMO Mobile Banking app that helps customers better manage money through personalized tips about spending, savings, and deposits.
ROLE: Lead Product Designer
🏆 Artificial Intelligence Excellence Award
Business Intelligence Group (2020)
🏆 Customer Financial Resilience Award
Celent Model Bank Awards (2021)
Impact
+18% increase in daily active users
47% of users reported feeling more confident
App store reviews mentioning ‘insights’ rose by 28% post-launch
9% higher cross-sell conversion
~7 million insights per month generated
New testing frame work for feedback
3 teams reused components
Customer problem
A 2018 BMO survey revealed that two-thirds of Canadians were financially stretched. Nearly half were paying down debt, and 37% of millennials cited social pressure as a barrier to saving. Customers lacked guidance and motivation to reach their goals.
“How might we reduce customers’ financial stress while empowering them to meet their goals?”
Discovery, insights & opportunities
I conducted a competitor tear down of 20 leading mobile finance apps. This included aspects such as cash flow forecasting, personalization, educational value of financial visualizations, frequency of notifications, Transparency of “available to spend” information.
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Most financial apps provide static balance updates without accounting for upcoming deposits or withdrawals. This leaves users with an incomplete view of liquidity.
Opportunity: Design a forward-looking “free-to-spend” view that projects available cash until payday.
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Competitors provide one-off charts with no ongoing reference point.
Opportunity: Introduce a persistent “spending so far” snapshot to ground users in real-time progress.
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Few products help users interpret spending patterns.
Opportunity: Compare monthly spending against historical behaviour to drive self-awareness and habit change.
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Notifications typically occur after transactions.
Opportunity: Surface proactive alerts when payments or subscriptions are higher than usual.
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Most balances ignore scheduled payments.
Opportunity: Create a “Free-to-Use” indicator that reflects truly disposable cash.
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Competitors visualize spending but don’t teach users what it means.
Opportunity: Offer a holistic financial snapshot to build literacy and confidence.
Design strategy
We aimed to move beyond transactional banking by helping customers understand their money. After analyzing 25+ products, we found most apps track spending but don’t build confidence or foresight. Our strategy focused on simplifying cash flow and building trust through transparency and education.
We aligned the team around 3 design pillars:
Predictive clarity - help users anticipate their balance before payday.
Personal relevance - tailor insights to spending habits, not generic advice.
Effortless understanding - visualize information in one glance, no financial jargon.
Persona explorations
Design explorations
We explored multiple ways to deliver insights within the banking experience. Each concept was guided by a clear hypothesis and tested for comprehension, frequency of use, and trust.
Concept A: Persistent Snapshot
We introduced a clear “Safe to Spend” amount and a countdown to payday, giving users immediate context for short-term planning.
Concept B: Insight Awareness
Concept A plus surfacing how many new insights were available, allowing users to explore personalized spending patterns and trends.
Concept C: Elevated insight visibilty
Lightweight insight feed directly on the home screen. Up to three rotating insight cards appeared above account summaries, allowing users to glance at recent financial learnings.
Through iterative testing, we evaluated which approach balanced relevance, visibility, and cognitive load, helping define where and how financial insights could best empower everyday decision-making.
Testing and iteration
We merged the strongest patterns from the initial concepts and prioritized user preferences revealed in testing. This included immediate access to account balances, and then insights categorized.
5 insight categories:
Good news: You have money to save
Just arrived: New money in your account
Heads-up: Money has been moved
Take a look: Warning something seems off
For review: Review spending over time
Evolved designs
More than 25 distinct insights
Savings-goals tracking insight was very well-loved. It’s been rated ~4.7/5 and helped over 100,000 goals get set.
“Review spending” and “new merchant charges” insights are top most used insights
CashTrack insight
To help customers improve their financial wellness, We also introduced BMO CashTrack Insight – an artificial intelligence (AI) driven capability that identifies potential cash shortfalls and helps customers better manage upcoming expenses. It made customers feel more secure about upcoming expenses.
Pre-approved line of credit
Real-time insights and pre-approved offers make borrowing simple, transparent, and timely.
Intelligent continuous feedback
The higher an insight is rated, the more often it will be seen along side other insights. Customers comments remained anonymous and used to improve insights that appeared in their feed.
Testing and validation
20 participants unmoderated testing using usertesting.com
Initial test with 300 BMO employees
24 moderated testing with customers
Launched to 1000 customers
Lauched to 10k, 50k, then 100k customers
Finally launched to all 8 million customers in Canada
Awards
Impact
+18% increase in daily active users
47% of users reported feeling more confident
App store reviews mentioning ‘insights’ rose by 28% post-launch
9% higher cross-sell conversion
~7 million insights per month generated
New testing frame work for feedback
3 teams reused components
Reflection & learnings
This project reinforced the value of designing with ambiguity, not against it. Early explorations (A, B, and C) taught us that users respond best when financial data feels personal yet predictable, seeing their account first anchored trust, while insights provided meaningful depth.
Collaborating closely with Product Manager, Data Scientists and Engineering teams also reshaped how I approached experimentation. Instead of shipping static UI, we built a framework for continuous testing and iteration, allowing insights to evolve as AI models improved.
Balancing trust and discoverability was key. Customers wanted clarity before curiosity. We learned that insights only add value when they’re secondary to control. This shaped how I now approach data-heavy products. Next phase would explore personalization of insights frequency and adaptive notification timing based on spending behaviour.