Life Actuarial Maths

Tools for creating and working with aggregate probability distributions.

An open-source Python framework for actuarial cash flow models

All Python algorithms published by Open Source Modelling in one place.

Easily Reference and use Actuarial Mortality Tables

Examples and Tutorials using JuliaActuary packages.

A handy tool for actuarial modeling, which is designed to achieve both accuracy and accountability.

Data collection and exploratory analysis related to COVID-19 for general insurance actuaries and the public

Classification of reserve risk with chain-ladder

Solving Actuarial Math with Python

Multi-Population Mortality Modeling With Neural Networks

All Matlab algorithms published by Open Source Modelling in one place.

n dimensional Brownian motion with an arbitrary mean and Variance Covariance matrix.

All JavaScript algorithms published by OSM in one place.

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

Black and Sholes model for simulating the stock market in Python.

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

This will house subprojects associated with research papers sponsored by the CAS

In this notebook we take a look at a relevant project that is frequently encountered by insurers: Fraud Detection. For this purpose we use a car data set from a public source and will show the necessary steps to establish an automated fraud detection.

Popular way to model the yield curve called Nelson-Siegel-Svannson algorithm.