🚀 FinFusion — (V1)

Version 1 of my final-year fintech project.
A privacy-first personal & group finance app for budgeting, transactions, Splitwise-style group splitting, explainable AI suggestions, and EWMA-based forecasting. Built for local prototyping (localStorage) with an easy path to server + DB.

Here's the link to the repo of the final build: https://github.com/marilyndsza/FinFusion-V2

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🔑 Description

A React-based personal finance tracker with budgeting, group-expense management, local AI heuristics for suggestions, and EWMA forecasting — privacy-first and production-ready to plug into a backend.

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📌 Features

• Create & manage monthly budgets by category
• Add transactions, view category spending per month
• Group-expense management (add people, split expenses, simplified settlements)
• EWMA forecasting per-category and total (configurable monthsBack & alpha)
• Local explainable heuristics to suggest reallocations, spot overspend/underspend
• Demo/seed mode for quick testing (localStorage-backed)
• Local-first privacy; optional backend for persistence

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🧩 Tech Stack

• Frontend: React, JSX, Tailwind CSS
• Persistence (prototype): localStorage (key: ai_budgets_data_v3)
• Forecasting / AI: EWMA heuristics in src/lib/budgetAI.js (replaceable with server-side ML)
• Optional Backend: Python (Flask / FastAPI) or Node/Express — repo contains backend/ hints
• Charts: Lightweight SVG sparklines (upgradeable to Recharts/Chart.js)

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📸 Screenshots

Dashboard ⬇️

Budgets Page ⬇️

Add Expense ⬇️

Group Expense ⬇️

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📁 Project structure (key files)

/frontend /src /components /ui AIBudgetSuggestions.jsx ForecastOverview.jsx /pages Budgets.jsx GroupExpenses.jsx Forecasting.jsx /lib budgetAI.js # generateForecasts, generateSuggestions (EWMA + heuristics) App.js index.js /backend server.py (or app.js) requirements.txt / package.json

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🔎 Forecasting & AI (Summary)

📈 Forecasting

• Uses EWMA (Exponentially Weighted Moving Average)
• Looks back over monthsBack (default 6–12 months)
• Adjustable alpha (0.2–0.6) for sensitivity tuning

🤖 AI Suggestions

• Explainable heuristic engine
• Detects overspend / underspend
• Suggests budget reallocations
• Includes numeric evidence for every suggestion

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🛠️ Run Locally (Dev)

Frontend & Backend

cd frontend
npm install     # first time
npm start       # opens http://localhost:3000

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cd backend
pip install -r requirements.txt
python server.py   # or: uvicorn app:app --reload / node server.js | or: uvicorn server:app --reload --port 5050 (mac)

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