Credit Rating & Investment Grade Prediction
Machine learning models to predict corporate credit ratings and classify investment-grade companies.
2025
Project Overview
This project focuses on predicting corporate credit ratings and determining whether a company falls into the investment-grade category using machine learning techniques. Credit rating prediction plays a critical role in financial decision-making, risk assessment, and investment strategies.
Working of Project
The dataset consists of financial indicators such as liquidity ratios, profitability metrics, and debt ratios. Data preprocessing included handling missing values, normalization, and feature selection. Multiple machine learning models including Logistic Regression and Neural Networks were trained and evaluated to classify companies into credit rating categories.
Key Features
- Credit rating classification (multi-class problem)
- Investment-grade prediction (binary classification)
- Feature engineering using financial ratios
- Model comparison and evaluation
- Data preprocessing and normalization
Technologies Leveraged
- Python
- Scikit-learn
- Pandas
- NumPy
- Matplotlib
- Neural Networks