Actuaries are well placed to introduce data science techniques to actuarial work, but face learning new tools, potentially in conjunction with larger datasets and more complex analytical pipelines. These challenges are also being faced in science and by other professions.
We hope we have convinced you that working reproducibly helps address the challenges of working in data intensive fields.
We make the case that actuaries should adopt these techniques to streamline how actuarial work is produced - freeing them to focus on adding value for their organisations and clients.
If you wish to introduce a reproducible process in your organisation:
- Take an existing process or report that is repeated often
- Develop a minimal viable solution using the tools and techniques introduced in the exercises
- Pilot it with colleagues and let others contribute to the project
- Share what you learn within your organisation
- Consider what you can share more widely e.g. with the actuarial community
About the authors
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Dr Matthew Forshaw is a Lecturer in Data Science at Newcastle University, and Data Skills Policy Leader at The Alan Turing Institute working on the Data Skills Taskforce. He is the Programme Director of Newcastle’s Industrial MSc in Data Science.
Philip Darke is an actuary with over 10 years’ consulting experience at Mercer. Philip believes data science will play a significant role in the future of the actuarial profession, and is currently studying at the EPSRC Centre for Doctoral Training in Cloud Computing for Big Data at Newcastle University.