R Resources for Actuaries & Insurance Analysts
This page is meant to be a resource for actuaries and analysts using R.
R is widely used by actuaries and insurance analysts. It is an extremely versatile open source programming language for statistical computing and graphics. R’s open-source nature, extensive package ecosystem, and active community make it an excellent tool for actuaries and insurance analysts who want to perform sophisticated data analysis, modeling, and visualization in their day-to-day work.
Here are some specific ways in which R can be beneficial for actuaries and insurance analysts:
- Data Analysis and Manipulation: R provides powerful tools for importing, cleaning, and manipulating data. Actuaries can use packages like dplyr and tidyr for data wrangling tasks.
- Statistical Modeling: Actuaries often need to build complex statistical models to analyze risk and predict future events. R offers a wide range of statistical modeling tools, including regression analysis, survival analysis, and time-series analysis.
- Data Visualization: R is excellent for creating high-quality data visualizations. Actuaries can use packages like ggplot2 to generate a wide variety of plots and charts, aiding in the interpretation and communication of results.
- Risk Management and Simulation: R is well-suited for simulating complex financial scenarios and assessing risk. Actuaries can use it for Monte Carlo simulations and other risk management techniques.
- Actuarial Science Packages: There are specific R packages designed for actuarial applications, such as lifetable and ChainLadder, which are useful for life insurance and reserving analysis.
- Machine Learning: With the increasing use of machine learning in insurance, actuaries can leverage R for implementing machine learning algorithms. Packages like caret and randomForest can be used for predictive modeling.
- Financial Analysis: R can be used for financial analysis, including calculations of present values, net present values, and various financial metrics relevant to insurance and actuarial work.
- Reproducibility and Documentation: R scripts provide a way to document and reproduce analyses. This is crucial for maintaining transparency and ensuring that analyses can be replicated or modified by others.
Online Resources
CRAN TASK Views
General Actuarial References
- Arthur Charpentier: Machine Learning & Data Science for Actuaries, with R
- Tommy Cornally: Building Pension Models and Actuarial Tools Using R and R Shiny
- Freakonometrics: Category Archives: Actuarial science
- J Schelldorfer: Deep Learning with Actuarial Applications in R
- Yiannis Parizas: Free for All
- Maria Prokofieva: R is for ActuaRies
- Nigel di Silva: An Introduction to R: Examples for Actuaries
Credibility Theory
- Jean-Philippe Boucher: Crédibilité: théorie et applications avec R
- Brazauskas et al: Credibility and Regression-Type Modeling
- Dutang et al: Credibility theory features of actuar
- Vincent Goulet: Credibility theory with R
Generalized Linear Models (GLM)
- Tyson S. Barrett: Chapter 5: Generalized Linear Models
- Qixiang Fang and Rens van de Schoot: Generalised Linear Models with glm and lme4
- Nathaniel E. Helwig: Generalized Linear Models in R
- Steve Midway: Chapter 8 GLMs: Generalized Linear Model
- Simon: Insurance Generalised Linear Models (GLMs) in R
- University of Madison: Generalized Linear Models in R
Risk Theory
- Katrien Antonio and Jonas Crevecoeur: Risk Modelling in Insurance : a collection of computer labs in R
- Kass et al: Modern Actuarial Risk Theory
Books Using R
Actuarial science using R references
- Charpentier, A., ed. (2014). Computational Actuarial Science with R, Chapman & Hall/CRC. doi:10.1201/b17230
- Kaas, R., Goovaerts, M., Dhaene, J. & Denuit, M. (2008). Modern Actuarial Risk Theory Using R, 2nd ed., Springer-Verlag. doi:10.1007/978-3-540-70998-5
- Bowers, N. L., Gerber, H. U., Hickman, J. C., Jones, D. A. & Nesbitt, C. J. (1997). Actuarial Mathematics, The Society of Actuaries.
- Teugels, J. & Sundt, B. (2004). Encyclopedia of Actuarial Science, Vol. 1, John Wiley & Sons. doi:10.1002/9780470012505
Life insurance references
- Dickson, D., Hardy, M. & Waters, H. (2013). Actuarial Mathematics for Life Contingent Risks, 2nd ed., Cambridge University Press. doi:10.1017/9781108784184
- Macdonald, A., Richard, S. & Currie, I. (2018). Modelling Mortality with Actuarial Applications, Cambridge University Press. doi:10.1017/9781107051386
Non-life insurance references
- Frees, E. (2009). Regression Modeling with Actuarial and Financial Applications, International Series on Actuarial Science, Cambridge University Press. doi:10.1017/CBO9780511814372
- Jong, P. D. & Heller, G. (2008). Generalized Linear Models for Insurance Data, Cambridge University Press. doi:10.1017/CBO9780511755408
- Klugman, S., Panjer, H. & Willmot, G. (2019). Loss Models: From Data to Decisions, 5th ed., John Wiley & Sons.
R Actuarial Jobs
Click here for an Actuary List is a job board for the actuarial profession that allows you to search through open job posting for the R programming language.
2024 Conferences and Meetings
| Conferences | Date | Location |
| Risk Theory Society Annual Seminar | April 19 – 21, 2024 | TBT |
| CAS Spring Meeting | May 5 – 8 , 2024 | Atlanta, Georgia |
| 12th Conference of Actuarial Science and Finance | May 20 – 25, 2024 | Karlovasi, Greece |
| International Conference on Mathematical Statistics and Actuarial Science (ICMSAS) | May 24 – 25, 2024 | NYC, USA |
| 5th European Congress of Actuaries | June 6 – 7, 2024 | Rome, Italy |
| Insurance Data Science Conference: Stockholm University, Dept. of Math. | June 17 – 18, 2024 | Stockholm, Sweden |
| Scandinavian Actuarial Conference | Aug 14 – 16, 2024 | University of Copenhagen, Denmark |
| European Actuarial Journal Conference | Sept 9 – 11, 2024 | Lisbon, Portugal |
| ICAFM 2024 International Conference on Actuarial and Financial Mathematic | Oct 4 – 5, 2024 | Tbilisi, Georgia |
| SOA ImpACT Conference | Oct 27 – 30, 2024 | National Harbor, MD, USA |
| CAS Annual Meeting | Nov 3 – 6, 2024 | Arizona Grand Resort & Spa in Phoenix, Arizona, USA |