Actuarial Science Python Packages

surpyval

A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.

cashflower

An open-source Python framework for actuarial cash flow models

actuarialpy

Core actuarial analysis tools for Python: experience analysis, per-exposure metrics, trend, completion, seasonality, credibility, exposure, and TVM.

lossmodels

Actuarial loss modeling in Python: severity, frequency, aggregate loss, fitted distributions, and insurance loss analytics.

ratingmodels

Pricing and rate-indication tools for Python: manual rating, experience rating, GLM relativities, retention gross-up, renewal, and audit trails.

aggregate

Tools for creating and working with aggregate probability distributions.

extremeloss

Extreme-value tail-risk estimation in Python: peaks-over-threshold, GPD fitting, rare-event analysis, and large-claim loading.

risksim

Portfolio Monte Carlo risk simulation in Python for insurance risk, aggregate loss, capital modeling, and risk measures.

actuarialmath

Python package to solve actuarial life-contingent risks

gemact

Repository of GEMAct source code. Enjoy!

lossratio

Loss ratio analysis and projection for long-term health insurance. In development.

insurance-scmoe

Spatially Clustered Mixture of Experts for joint frequency-severity insurance pricing