Insurance Data Notebook

All Jupyter Notebooks implemented by Open Source Modelling in one place.

Notebooks supporting investigations in U.S. healthcare data.

Validation checks for EIOPA technical submissions written and documented in Jupyter notebooks.

Notebook sample of Exploratory Data Analysis (EDA) for Prudential Life Insurance Sample Data

An interactive insurance policy query-answering notebook with a Retrieval-Augmented Generation (RAG) pipeline with semantic search, caching, and GPT-based response generation.

The study Machine-Learning Methods for Insurance Applications is dedicated to the question of how new developments in the collection of data and their evaluation in the context of Data Science in the actuarial world can be utilized. The results of the study are based on the R language, so the first goal of this work is to reproduce the calculati…