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!
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
.. _modelx: http://docs.modelx.io