🚀 FinSight — SME Financial Health Analyzer (Stage 1)

📌 Overview

FinSight is an AI-powered financial analysis platform designed to evaluate the financial health of Small and Medium Enterprises (SMEs).

In Stage 1, the focus is on building a working prototype that:

• Extracts financial data from uploaded documents
• Validates basic accounting consistency
• Computes key financial ratios
• Generates a simple financial health overview

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🎯 Problem Statement

SMEs often struggle with:

• Understanding financial health
• Access to structured financial insights
• Manual and error-prone financial analysis

FinSight solves this by automating extraction + analysis using AI.

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🧠 Stage 1 Features

✅ Document Processing

• Upload financial documents (PDF/Image)
• Extract structured financial data using OCR

✅ Data Validation

• Basic accounting check:

  • Assets = Liabilities + Equity

✅ Financial Analysis

• Key ratio calculations:

  • Profit Margin
  • Debt-to-Equity Ratio
  • Current Ratio

✅ AI Integration (Basic)

• Structured response using Groq (LLaMA)
• JSON-based output

✅ Simple Dashboard

• Upload → View extracted data → See results

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🏗️ Project Structure

finsight/
├── backend/
│   ├── app/
│   │   ├── main.py
│   │   ├── api/routes.py
│   │   ├── core/
│   │   ├── schemas/
│   │   ├── services/
│   │   └── utils/
│   ├── requirements.txt
│   └── .env
│
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   ├── hooks/
│   │   ├── context/
│   │   ├── pages/
│   │   ├── FinSight.jsx
│   │   └── theme.js
│   ├── package.json
│   └── vite.config.js
│
└── README.md

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⚙️ Tech Stack

Backend

• FastAPI
• Python
• Pydantic
• OCR (Tesseract / equivalent)
• Groq API (LLaMA 3)

Frontend

• React (Vite)
• JavaScript
• Context API

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🚀 Getting Started

🔧 Backend Setup

cd backend
python -m venv venv
venv\Scripts\activate   # Windows
# or
source venv/bin/activate  # Mac/Linux

pip install -r requirements.txt

Create a .env file:

GROQ_API_KEY=your_api_key_here

Run the backend:

uvicorn app.main:app --reload

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💻 Frontend Setup

cd frontend
npm install
npm run dev

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🔌 API Endpoints (Stage 1)

📤 Upload & Extract

POST /extract

• Input: File (PDF/Image)
• Output: Extracted structured financial data

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📊 Analyze Financial Data

POST /analyze

• Input: JSON financial data
• Output: Financial ratios + basic score

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🧪 Sample Workflow

1. Upload financial document
2. Extract data via OCR
3. Verify/correct data (optional UI)
4. Run analysis
5. View financial insights

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⚠️ Limitations (Stage 1)

• Basic OCR accuracy (no advanced correction yet)
• Rule-based analysis (no ML models)
• Limited financial metrics
• No historical trend analysis

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🔮 Future Improvements

• ML-based financial scoring (XGBoost/Random Forest)
• SHAP explainability
• Industry benchmarking
• Forecasting (12-month projections)
• PDF report generation

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👨‍💻 Team Notes (Hackathon Strategy)

• Focus on working prototype over perfection

• Ensure:

  • End-to-end flow works ✅
  • UI is clean and simple ✅
  • Demo is smooth ✅

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📜 License

This project is for educational and hackathon purposes.

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⭐ Final Note

FinSight is built to simplify financial intelligence for SMEs using AI.

Stage 1 = Foundation. Execution matters more than complexity.