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Actuarial models in Python

Project description

lifelib is a collection of open-source life actuarial models written in Python. lifelib includes a variety of models, with sample scripts and Jupyter notebooks that demonstrate how to use the models.

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What for?

lifelib models are highly versatile and transparent. You can customize lifelib models and utilize them in various practical areas, such as:

  • Model validation / testing

  • Pricing / profit testing

  • Research / educational projects

  • Valuation / cashflow projections

  • Asset-liability modeling

  • Risk and capital modeling

  • Actuarial modernization to replace spreadsheet models

Why lifelib?

By effectively utilizing the models in lifelib, you can expect the following benefits from both model development and governance perspectives:

  • A more efficient, transparent, and faster model development experience

  • Model integration with the Python ecosystem (Pandas, Numpy, SciPy, etc.)

  • Elimination of spreadsheet errors

  • Improved version control and model governance

  • Automated model testing

Some of the models in lifelib are built using modelx, an open-source Python package for building object-oriented models in Python. By using lifelib, you can enjoy the following advantages:

  • Models run fast!

  • Formulas are easy to read

  • Easy to trace formula dependency and errors

  • Formulas are instantly evaluated

  • Pandas and Numpy can be utilized

  • Object-oriented

  • Input from Excel and CSV files

  • Documents can be integrated

  • Formulas are saved in text files

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Source Distribution

lifelib-0.9.2.tar.gz (16.2 MB view hashes)

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Built Distribution

lifelib-0.9.2-py3-none-any.whl (16.5 MB view hashes)

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