Financial Risk Assessment

Portugues | English

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Portugues

Visao Geral

Ferramenta de classificacao de risco financeiro usando Python e scikit-learn. Um unico script (src/main.py, 168 linhas) que carrega dados financeiros de um CSV, pre-processa as features, treina um RandomForestClassifier para prever niveis de risco (baixo, medio, alto) e gera metricas de avaliacao.

Funcionalidades

• Carregamento de dados a partir de arquivo CSV (ou geracao de dados de exemplo)
• Pre-processamento: preenchimento de valores ausentes (media para numericos, moda para categoricos) e one-hot encoding
• Treinamento de modelo RandomForestClassifier
• Avaliacao com acuracia e relatorio de classificacao
• Testes unitarios com pytest

Arquitetura

graph LR
    A[Dados CSV] --> B[Pre-processamento]
    B --> C[Treinamento RandomForest]
    C --> D[Avaliacao]
    D --> E[Acuracia + Relatorio]

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Como Usar

Pre-requisitos

• Python 3.12+
• pip

Instalacao

git clone https://github.com/galafis/Financial-Risk-Assessment.git
cd Financial-Risk-Assessment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt

Execucao

python src/main.py

O script gera um CSV de exemplo (financial_data.csv), treina o modelo e exibe a acuracia e o relatorio de classificacao no terminal.

Testes

pytest tests/

Estrutura do Projeto

Financial-Risk-Assessment/
├── src/
│   ├── __init__.py
│   └── main.py          # Script principal (168 linhas)
├── tests/
│   └── test_main.py     # Testes unitarios
├── .gitignore
├── LICENSE
├── README.md
└── requirements.txt

Stack

Tecnologia	Uso
Python	Linguagem principal
pandas	Manipulacao de dados
scikit-learn	Treinamento e avaliacao do modelo
pytest	Testes unitarios

Licenca

Este projeto esta licenciado sob a Licenca MIT - veja o arquivo LICENSE para detalhes.

Autor

Gabriel Demetrios Lafis

• GitHub: @galafis
• LinkedIn: Gabriel Demetrios Lafis

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English

Overview

Financial risk classification tool using Python and scikit-learn. A single script (src/main.py, 168 lines) that loads financial data from a CSV, preprocesses features, trains a RandomForestClassifier to predict risk levels (low, medium, high), and outputs evaluation metrics.

Features

• Load data from CSV file (or generate sample data)
• Preprocessing: fill missing values (mean for numeric, mode for categorical) and one-hot encoding
• Train a RandomForestClassifier model
• Evaluate with accuracy score and classification report
• Unit tests with pytest

Architecture

graph LR
    A[CSV Data] --> B[Preprocessing]
    B --> C[RandomForest Training]
    C --> D[Evaluation]
    D --> E[Accuracy + Report]

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Usage

Prerequisites

• Python 3.12+
• pip

Installation

git clone https://github.com/galafis/Financial-Risk-Assessment.git
cd Financial-Risk-Assessment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt

Run

python src/main.py

The script generates a sample CSV (financial_data.csv), trains the model, and prints accuracy and classification report to the terminal.

Tests

pytest tests/

Project Structure

Financial-Risk-Assessment/
├── src/
│   ├── __init__.py
│   └── main.py          # Main script (168 lines)
├── tests/
│   └── test_main.py     # Unit tests
├── .gitignore
├── LICENSE
├── README.md
└── requirements.txt

Stack

Technology	Usage
Python	Core language
pandas	Data manipulation
scikit-learn	Model training and evaluation
pytest	Unit tests

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Gabriel Demetrios Lafis

• GitHub: @galafis
• LinkedIn: Gabriel Demetrios Lafis