3 papers
stat.ME2023
A machine learning approach based on survival analysis for IBNR frequencies in non-life reserving
Munir Hiabu, Emil Hofman, Gabriele Pittarello
We introduce new approaches for forecasting IBNR (Incurred But Not Reported) frequencies by leveraging individual claims data, which includes accident date, reporting delay, and po…
stat.AP2023
Individual claims reserving using the Aalen--Johansen estimator
Martin Bladt, Gabriele Pittarello
We propose an individual claims reserving model based on the conditional Aalen-Johansen estimator, as developed in Bladt and Furrer (2023b). In our approach, we formulate a multi-s…
stat.AP2023
GEMAct: a Python package for non-life (re)insurance modeling
Gabriele Pittarello, Edoardo Luini, Manfred Marvin Marchione
This paper introduces , a package for actuarial modelling based on the collective risk model. The library supports applications to risk costing a…