Life actuarial models in Python
lifelib is a collection of open-source life actuarial models. lifelib includes a variety of models, with sample scripts and Jupyter notebooks to 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
- Asset-liability modeling
- Risk and capital modeling
- Actuarial modernization to replace spreadsheet models
lifelib models 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
Consequently, you can expect following benefits from model development and governance perspectives:
- More efficient, transparent and faster model development
- Model integration with Python ecosystem (Pandas, Numpy, SciPy, etc..)
- Spreadsheet error elimination
- Better version control / model governance
- Automated model testing
Copyright (c) 2021 lifelib Developers
lifelib is free software; you can redistribute it and/or modify it under the terms of MIT License.
Contributions, productive comments, requests and feedback from the community are always welcome. Information on lifelib development is found at Github https://github.com/fumitoh/lifelib
- Python 3.6+
- modelx
- networkx 2.0+
- Pandas
- OpenPyXL
lifelib is in its early alpha-release stage, and its specifications are subject to change without consideration on backward compatibility.
lifelib was originally written by Fumito Hamamura and it was first released on January 2nd, 2018.