Inspiration
Many young adults understand the importance of financial literacy and investing, but they often don't know where to start. As a result, they tend to put it off until it feels too late. LearnETF was born out of the need to provide the next generation of investors with accessible and engaging resources to help them take control of their financial future.
What it does
The app takes user input to personalize financial literacy modules based on their experience level with investing. Each module includes both a static and an interactive component. The static component provides up-to-date information, while the interactive part allows users to simulate potential returns on specific trades using historical stock market data. This hands-on approach helps users build confidence in their investment knowledge.
How we built it
We used a mix of technologies to bring LearnETF to life, including:
OpenAI models process raw data and classify users based on their experience
Plotly to create dynamic, easy-to-understand data visualizations
Python with Flask API to power the backend and handle integration
Next.js and Tailwind to build a sleek and responsive frontend
Challenges we ran into
One of the biggest challenges we faced was not having enough time to incorporate a Voiceflow AI agent that could act as a personal tutor for users. This feature would have added an extra layer of interactivity and support, helping users navigate their financial learning journey more effectively.
Accomplishments that we're proud of
We're really proud of how well we executed our plan, managed our time, and collaborated as a team. We divided tasks efficiently and worked together seamlessly to achieve our goals. Seeing our ideas come to life in such a short period of time was incredibly rewarding, especially since it was many of our first hackathons.
What we learned
Throughout this process, we learned a lot about backend development and server integration. We explored things like:
Optimizing API interactions to ensure smooth communication between the frontend and backend
Implementing security features to protect user data
Using cloud-based solutions to enhance performance and scalability
These insights will definitely come in handy as we continue to develop and improve Securities Educator.
What's next for LearnETF
We would like to take LearnETF to the next level by:
Integration into Sun Life Financial services: We see great potential in incorporating our platform within Sun Life's existing ecosystem to provide their clients with valuable financial education.
AI Chatbot: Adding an AI-powered chatbot that could assist users with their questions not just within the app, but also on the general Sun Life website.
Predictive Analytics: Developing tools to estimate the future value of trades, helping users make smarter investment decisions based on data-driven insights.
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