Loss modelling framework.
-
Updated
Nov 29, 2024 - Python
Loss modelling framework.
Repository of GEMAct source code. Enjoy!
Functions from the book "Reinsurance: Actuarial and Statistical Aspects"
Destruction rate modeling with the Maxwell Boltzmann Bose Einstein Fermi Dirac (MBBEFD) distribution
SCOR Datathon in 2020. Acquired and processed open data, predicted level of Glycohemoglobin, Cholesterol and probability of diabetes, then identified the probability change with Random Survival Forest to suggest improvements to a user.
File validation and data sampling toolkit for the Simplitium Open Exposure Data (OED) (re)insurance exposure data format
Prediction of market premiums for property damage and business interruption insurance products. Added natural hazard data and stacked 3 best models as the final model.
Open reinsurance data - be independent and create insights.
You will be able to execute transactions against a real Hyperledger Fabric blockchain network for Reinsurance Claims that interacts with a blockchain network.
This Module tries to combine and simplify all aspects of Reinsurance Invoicing, Analysis, Slip Generation, Quotation & Data science. Later to be Intergrated into a cross platform API.
Information on reinsurance - market, analytics, and software.
A Dask library for Big Data processing in Python demo
A domain specific language for re/insurance contracts
Add a description, image, and links to the reinsurance topic page so that developers can more easily learn about it.
To associate your repository with the reinsurance topic, visit your repo's landing page and select "manage topics."