FinQuest

Inspiration

Most budgeting apps focus on numbers, but not meaning. We were inspired by how platforms like Spotify Wrapped turn data into something engaging, personal, and easy to understand. We wanted to bring that same experience to personal finance — transforming raw transaction data into a story about your habits and behavior.

What it does

FinQuest is a “Financial Wrapped” app that analyzes transaction data and turns it into a personalized spending identity.

Users upload a CSV of their transactions, and the app:

classifies spending into categories
identifies behavioral patterns
generates an AI-powered spending persona
highlights key habits and trends
provides actionable recommendations

All of this is presented in a wrapped-style, interactive UI that makes financial reflection more engaging and intuitive.

How we built it

We built FinQuest using:

Next.js (frontend and backend)
JavaScript
OpenAI API for generating insights and personas

The pipeline works as follows:

CSV data is uploaded and parsed client-side
Transactions are enriched and categorized
A summary of spending is generated
This data is sent to the OpenAI API
The AI returns structured insights, identity, and recommendations
The frontend renders everything in a wrapped-style experience

We also added gamified elements like character pulls and a leaderboard to make the experience more engaging.

Challenges we ran into

Ensuring reliable AI responses in a strict JSON format
Integrating a static HTML prototype into a dynamic Next.js app
Managing environment variables securely during deployment

Accomplishments that we're proud of

Successfully combining AI insights with real financial data
Creating a unique “financial identity” concept instead of a traditional dashboard
Building a fully working CSV upload → AI → wrapped pipeline
Designing a cohesive, interactive UI within a short hackathon timeframe
Deploying a live version for judges to test
Submitting Anything at all! (We've never done a hackathon before!)