Data Tech June 3, 2025

SmartSaver: Bank Calculator Tool

Developed an analytics decision platform that transforms complex banking data into actionable financial insights, empowering users to optimize their savings strategy through personalized calculations and an innovative fund distribution algorithm.

Task

Conceptualized, designed, and developed a comprehensive banking calculator tool that enables users to compare interest rates and potential returns from different banks, considering multiple qualification criteria.

  • Role

    Product Owner & Developer

  • Tech

    React, Tailwind CSS, Supabase, Framer Motion

Open Project
Discovery

User Research & Insights

My discovery process began with a key insight: despite the abundance of financial comparison websites, none effectively addressed the multi-variable qualification criteria that determine actual interest returns.

Through structured interviews with 15 potential users across different financial profiles, I uncovered three critical user pain points:

  • Calculation Complexity: “I can’t manually calculate all these conditional tiers across different banks.”
  • Optimization Challenge: “Should I put all my money in one bank or split it? I have no way to figure this out.”
  • Information Asymmetry: “Banks make their interest structures deliberately complicated to prevent easy comparison.”

Competitive analysis revealed most existing calculators only calculate single bank returns without comparative analysis, ignore multi-variable qualification conditions, present raw numbers without actionable insights, and lack fund distribution optimization capabilities.

Personas

User Personas & Jobs

Through research, I identified four primary user personas:

Persona 1: Beginner Saver
Young, tech-savvy professional
  • Looking to save for a BTO flat down payment in the next 2-3 years
  • Already has credit cards with several banks but isn’t strategically using them to qualify for higher interest rates
  • Prefers digital solutions for financial management

“I need to understand how different banking decisions will affect my financial future.”

Persona 2: Time-Pressed Tactician
Mid-career professional with children
  • Manages family finances and wants to optimize returns without spending hours researching
  • Has insurance policies and uses GIRO for utility bills and children’s school fees
  • Time-constrained and needs quick, clear financial information

“I need to quickly determine which bank will give me the best return for my specific situation”

Persona 3: Optimization Seeker
Small F&B business owner
  • Has fluctuating monthly income
  • Uses multiple banks for business and personal finances
  • Interested in optimizing distribution of funds across banks to maximize interest while maintaining liquidity
“I need to optimize my banking setup to maximize interest without spending hours on calculations”
Persona 4: Retiree
Has substantial savings of $200,000+
  • Less comfortable with technology but willing to use intuitive digital tools
  • Looking for ways to generate passive income through interest as she transitions to retirement
  • Concerned about minimum balance requirements and maintaining access to funds

“I want to keep my money with me but try to maximise my savings. I don’t understand all these banking terms and conditions.”

Strategy

Product Vision & Strategy

Based on user research, I developed a clear product vision: “To empower users to make optimal banking decisions through transparent analysis of complex interest structures.”

This vision guided four strategic pillars:

  • Comprehensive Analytics Engine: Account for all conditional factors impacting interest rates
  • Insight Transformation: Convert complex calculations into clear comparative insights
  • Optimization Intelligence: Develop algorithms to determine optimal fund distribution
  • Continuous Learning: Collect anonymous usage data to enhance calculations

For feature prioritization, I developed a comprehensive feature set and prioritized it using a value-effort framework, focusing first on high-value, lower-effort features for the MVP, such as the multi-bank interest calculator, side-by-side comparison table, mobile-responsive interface, and basic feedback collection system.

Design

Analytics-First Design

Unlike typical calculators that simply present data, I took an analytics-first design approach focused on transforming raw calculations into actionable insights. This included creating a logical flow from input variables to insight presentation, developing progressive disclosure hierarchy for complex information, and designing a comparative visualization framework highlighting key differences.

The technical architecture was designed to support complex calculations while maintaining performance and scalability:

  • Modular Calculation Engine: Separated core calculation logic from presentation layer
  • Data Management: Used Supabase for structured storage of rates and criteria
  • Performance Optimization: Implemented calculation memoization to improve response time
  • Analytics Implementation: Designed event tracking for feature usage patterns
Analytics

Measurement Framework

I established a comprehensive measurement framework to evaluate product success, focusing on these primary metrics:

  • User Confidence Score: Measured through post-calculation survey
  • Decision Time: Time from initial visit to completion of comparison
  • Optimization Value: Percentage improvement through fund distribution optimization
  • Satisfaction Rating: Post-usage satisfaction survey results

I implemented a robust analytics architecture to measure both usage and impact, with an event tracking framework aligned with the user journey, a feedback collection system, and performance monitoring for calculation response time.

Security

Security Implementation

Input Sanitization
  • DOMPurify Implementation: Added robust sanitization for all user inputs, configured to strip HTML tags and attributes to prevent XSS attacks
  • Client-Side Sanitization: Sanitized user inputs in chat messages and calculator inputs before processing
  • Server-Side Sanitization: Implemented middleware to sanitize all incoming requests including body, query parameters, and URL parameters
Rate Limiting
  • API Rate Limiting: Implemented rate limiting on sensitive APIs (5 requests per minute per user) to prevent abuse
  • User Experience: Added user-friendly error messages and visual styling for rate limit notifications
Authentication Security
  • Supabase Authentication: Implemented secure email/password authentication with Google OAuth integration
  • Auth Flow Protection: Created secure authentication redirects and properly managed sessions and tokens
  • Production Configuration: Configured OAuth providers to only accept redirects to trusted domains
API & Data Security
  • CORS Configuration: Properly configured CORS headers to restrict API access to trusted domains
  • Secure Error Handling: Implemented error handling that doesn’t leak implementation details
  • Input Validation: Added checks for input types and formats before processing
  • Protected Routes: Implemented access controls to protect sensitive functionality
Analytics

Results & User Impact

Early results demonstrate significant impact on user financial decision-making:

  • 76% of users report increased confidence in their banking decisions
  • Average optimization value of 21% through the fund distribution algorithm
  • Decision time reduced by 89% compared to manual comparison methods
  • 4.7/5 average satisfaction rating from post-usage surveys

User feedback revealed several key insights: transparency drives trust, with users particularly valuing understanding exactly how interest is calculated; the fund distribution optimization feature receives the highest satisfaction ratings; and mobile usage exceeds expectations, with 68% of users accessing the tool via mobile devices and spending 24% more time exploring different scenarios.

Product Roadmap

Evolution & Future Plans

SmartSaver has evolved significantly from its initial concept, with each release adding valuable functionality based on user feedback and strategic priorities:

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