A framework for applying data science techniques to health and care actuarial projects

Johannes Michiel Luteijn, Jacky Tam, Rebecca Denis, Fiona Fan, Jaskaran Minhas, Dhanesh Kadan Puthanveedu and Abigail Takyi

British Actuarial Journal, 2026, vol. 31, -

Abstract: The fast-moving field of data science is increasingly permeating into the health and care actuarial sciences. Given this context, the Institute and Faculty of Actuaries set out to form a “techniques in data science in health and care” working party. This working party was tasked with creating a framework for those actuaries working within the health and care domain that would assist them in determining which techniques are appropriate for a project. The framework presented here was developed through a combination of literature review and synthesis of expert opinion from experienced practitioners from diverse backgrounds. The framework offers a structured, itemised approach, serving as a checklist to ensure that all relevant analytics and decisions are considered and documented. Each itemised topic is covered by a summary providing guidance and relevant references for further reading. The checklist follows the natural workflow of a data analytics project, guiding users through each step to prevent omissions and maintain rigour in both analysis, reporting and peer-review. The framework blends relevant analytics elements from actuarial science, data science and epidemiology. We hope the framework will enhance transparency, reproducibility, and comprehensiveness in the reporting and peer-review of health and care data analytics projects.

Date: 2026
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