FinSight was inspired by the growing need for accessible personal finance tools, especially for young adults navigating budgeting, saving, and investing. It’s a smart financial assistant that connects to users’ bank accounts via Plaid API, analyzes spending patterns, forecasts upcoming expenses using a machine learning model built with Python and delivers personalized financial insights. Built with a React.js frontend, Node.js/Express backend, and MongoDB for data storage, FinSight presents a clean, user-friendly interface powered by real-time data. Along the way, we tackled challenges like secure OAuth integration, data privacy, model tuning, and UX design. We're proud to have achieved over 80% prediction accuracy, implemented encryption for user data, and created an intuitive platform that makes finances feel less intimidating. Throughout the process, we deepened our skills in data handling, API integration, and secure web development. Looking ahead, we plan to expand FinSight with features like investment tracking, gamified savings goals, and multi-currency support to help users worldwide gain financial confidence.
Built With
- deepseekapi
- faiss
- langchain
- lucide-react-native
- openai
- python
- ragmodel
- react-native
- react-native-chart-kit
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