Launch: Actuartech Academy

Launch: Actuartech Academy

We are happy to announce the launch of Foundations in R for Actuaries and Case Study: Lapse Rate Analysis. These two courses are decided by actuaries, for actuaries and are suitable for actuarial teams and students looking to improve their knowledge of the R programming language in an actuarial context.

Each of our courses (and future courses) are presented through fully-interactive Jupyter Notebooks that run directly in your browser - no need to install 3rd party software. These will allow you to edit pre-existing code and generate new code as you work through the course. In addition, we provide an RStudio IDE directly in your browser for you to use.

Foundations in R for Actuaries

This course guides you through the data science pipeline as it applies to the R programming language. We believe in building programming skills from the ground up so we dive into base R before exploring R's wealth of packages. We establish programming fundamentals and building blocks which will allow you to tackle R projects logically and apply these techniques to other programming languages you may wish to learn in the future

The course is structured as follows

  1. Getting Started: An introduction to R, data science, and the tools used
  2. Problem Specification: How R can help your business and simple use cases
  3. Data Collection: Programming fundamentals, using R's data structures, importing external data, and using R's internal datasets
  4. Data Management: Conditionals, loops, and creating functions
  5. Model Building: Using mathematical and statistical models in R, including built-in statistical distributions and functions
  6. Data Visualisation: Various methods of visualising data in R

For more information or if you would like to register, please click here.

Figure 1: Foundations in R for Actuaries

Case Study: Lapse Rate Analysis

We present an end-to-end walk through investigating lapse rates in a life insurance context. A lapse is when a policyholder either defaults on their premium payments or otherwise cancels their policy before the term has ended or claim. We make use of publicly available Society of Actuaries data on policy lapses and guide you through cleaning the data, preliminary visualisations, feature engineering, fitting models, and reporting and interpreting results.

The course is structured using the data science pipeline as follows:

  1. Introduction: What are lapses and why be concerned about them, and an overview of the data source
  2. Problem Specification: What we set out to solve, overview and initial checks on the data, and the external packages we will be using
  3. Data Collection and Management: Preliminary visualisations and analysis, feature engineering
  4. Model Fitting: Fitting the data to various models including multiple linear regression, regression trees, and random forests
  5. Reporting: Performance comparison and merits of the models and approaches used, further recommendations and a feedback loop for next steps

For more information or if you would like to register for the lapse analysis case study in R, please click here.

Or, if you would like to register for both the Foundations in R Course and the lapse analysis case study, please click here.

Figure 2: Case Study: Lapse Rate Analysis

Future Courses

We are still hard at work putting together future courses and case studies to be released. We are building fundamental courses for actuaries in Python, SQL, and IT domains. We are also developing case studies to explore mortality, retirement benefits, and non-life topics.

Resource Library

By signing up, you also get access to a resource library containing webinars and papers created by Actuartech and their partners on topics around data science, reporting, and principle-based learning material.

Contact us for more information. We also work with teams and business units to create bespoke training solutions.

Copyright © *Actuartech, January 2021*

Launch: Actuartech Academy

Written by Valerie Du Preez

This post was certified by Actuartech on

Review: This article is well-researched and provides valuable information.

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