GEMAct is a comprehensive actuarial package, based on the collective risk theory framework, that offers a set of tools for non-life (re)insurance costing, stochastic claims reserving, and risk aggregation.
The variety of available functionalities makes GEMAct modeling very flexible and provides actuarial scientists and practitioners with a powerful tool that fits into the expanding community of Python programming language.
Please visit our website to see our documentation and tutorial.
The pre-print of the accompanying paper is now available.
Previous versions were presented at the Mathematical and Statistical Methods for Actuarial Sciences and Finance 2022, and at the Actuarial Colloquia 2022, in the ASTIN section.
We want to especially thank the students in Statistica per le assicurazioni, M.Sc. in Economia e Finanza, at the Università Milano-Bicocca for having tested the package.