Actuarial models in Python
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.
Visit https://lifelib.io for more information!
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
Risk and capital modeling
Actuarial modernization to replace spreadsheet models
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
Input from Excel and CSV files
Documents can be integrated
Formulas are saved in text files
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