INDUSTRY:
BANKING
CLIENT:
WESTPAC HACKATHON
YEAR:
2024
EXPERIENCE:
REACT.JS, MACHINE LEARNING, AI
Westpac Auto Banking
about.
The Auto Paycheck Splitting App was developed over an intensive two-day sprint during the Westpac Hackathon, leveraging modern frontend technologies and AI integration to address personal finance challenges through automation and intelligent budgeting.
Frontend Architecture
Developed using React.js, enabling a dynamic and responsive single-page application.
Designed with a mobile-first approach, focusing on usability, clarity, and performance.
Included interactive UI components (sliders, pie charts, input validation) to enhance user engagement and provide real-time feedback on paycheck allocations.
AI-Driven Budgeting
Integrated with the OpenAI API to simulate a personalized financial assistant.
AI models were trained with budgeting heuristics and financial logic to:
Analyze user input and financial goals
Suggest optimal allocation strategies (e.g., 50/30/20 budgeting principle)
Adapt recommendations based on user-defined priorities (e.g., savings, bills, rent)
Scalability & Banking Integration
While direct bank account linking was out of scope during the hackathon, the application was architected with scalability and security in mind:
Designed for seamless integration with open banking APIs (e.g., Westpac’s API ecosystem)
Mocked secure authentication and authorization workflows using OAuth 2.0 principles
Structured data models to support encrypted, token-based access for personal financial data
outcome and challenges
Despite the condensed 48-hour timeframe of the Westpac Hackathon, the team successfully delivered a fully functional prototype that showcased the core concept of automated paycheck allocation powered by AI. The project stood out for its strong technical foundation, thoughtful user experience design, and real-world applicability in the personal finance space.
Key Outcomes:
Delivered a complete, interactive prototype with real-time paycheck splitting functionality.
Demonstrated intelligent budget recommendations through OpenAI’s API integration.
Designed a future-ready architecture to support secure integration with open banking APIs.
Challenges Overcome:
Time Constraints: Built the application end-to-end within two days, requiring rapid decision-making and agile development practices.
AI Prompt Engineering: Tuned prompts and structured inputs to simulate accurate financial behavior within OpenAI’s response framework.
Scalability Considerations: While bank integration was beyond scope, the system was thoughtfully designed to support OAuth 2.0 workflows and data encryption best practices in future development.
This project not only demonstrated technical proficiency and innovation under pressure, but also reinforced the potential of combining AI and fintech to empower users with smarter financial tools.
