AI Financial Advisor for Students ( finwise)

Main dashboard of FinWise showing real-time financial health, including income, expenses, money score, goals, and AI overspend alerts.
Add and manage expenses/income with categories, amounts, and history to track real financial data used by AI analysis.
AI-powered financial analysis showing spending trends, income vs expenses, savings rate, and key insights from user data.
Gemini-powered saving plan that creates a personalized weekly roadmap with actionable steps to achieve financial goals efficiently.
Time Machine feature predicting future savings and goal completion with interactive projections across different time horizons.

Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for AI Financial Advisor for Students ( finwise)

Inspiration

Every student knows the feeling — checking your bank account mid-month and feeling your heart drop. Most financial tools are built for salaried professionals, not students managing pocket money, mess bills, and irregular expenses.

We built FinWise because we faced this problem ourselves. We wanted something simple, smart, and actually useful for student life.

What it does

FinWise is a Google Gemini-powered AI financial advisor built specifically for students.

It takes your income and expenses and uses AI to:

Analyze spending habits and detect money leaks
Generate personalized weekly saving plans
Recommend beginner-friendly SIP investments with projected returns
Predict next month’s budget
Provide real-time financial advice through an AI chatbot (FinBot)

It also includes features like overspend alerts, goal tracking, receipt scanning, and a Money Score to gamify financial health.

How we built it

We built FinWise as a single-page web app using React and Tailwind CSS for a clean and responsive UI.

Google Gemini (gemini-2.0-flash) powers all the intelligence in the app. Instead of using AI just as a chatbot, we integrated Gemini deeply across multiple features including spending analysis, saving plans, SIP recommendations, budget prediction, and real-time chat.

We used structured prompts and real user financial data to generate meaningful and personalized outputs. Charts and visualizations are handled using Recharts, and the app is deployed on Vercel.

Challenges we ran into

One of the biggest challenges was managing multiple Gemini API calls while keeping the app fast and responsive. Since several features depend on AI, we had to carefully handle request timing and optimize prompt structure.

We also ensured that responses were not generic by feeding structured financial data into Gemini, making outputs more accurate and relevant.

Accomplishments that we're proud of

We successfully built a fully functional AI-powered financial assistant within a hackathon timeframe.

One feature we are especially proud of is the "Time Machine", which visualizes a student’s financial future in an engaging way. Unlike traditional finance apps, FinWise feels interactive, personalized, and actually fun to use.

Most importantly, this is not just a demo — it is a real product that students can start using immediately.

What we learned

We learned that AI becomes significantly more powerful when used as the core logic of an application rather than just an add-on feature.

Using Gemini across multiple workflows showed us how versatile it is in solving real-world problems, especially when combined with structured data and clear prompts.