About The Project

There are many great libraries providing credit risk analysis tools on github.
However, I couldn't find one that can cover all my needs. Hope you'll find it useful for your projects.

Here are the tools available in the library:

• Binning tool for both categorical and numerical features
• Feature selection tool for linear regression
• Basic optimization algorithms for credit portfolio management

Built With

Here are the libraries used for the project.

• numpy
• pandas
• scikit-learn

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Getting Started

Prerequisites

For using the library you need the following things

• python 3
• install pip or clone the git repository

Installation

Bellow is the installation command using pip

pip install risk-modeling-tools

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Usage

The library may be used for scoring models developing and credit risk analysis

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Roadmap

• Add Changelog
• Add Additional Templates w/ Examples

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Mikhail Gritskikh - @m_gritskikh - m.gritskikh@gmail.com

Project Link: https://github.com/mgrts/risk_modeling_tools

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Acknowledgments

Some useful links for better understanding

• Score Cards
• WoE and IV

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