Actuarial H&S science

The adage “knowledge is power” rings especially true for health and safety (H&S) professionals. Because this rapidly-evolving field deals with inherently substantial risks, the more you know, the better prepared you are to mitigate and manage those risks and keep workers safe.

The primary objectives of organisational H&S are to prevent any employee from experiencing material impairment of health, diminished functional capacity, or reduced life expectancy due to their employment. The legal terminology found in occupational H&S regulations – words like “shall”, “will”, or “must” – typically serves as the definitive framework for addressing no-fault or strict liability considerations.

Actuaries provide valuable insight to insurance companies with their predictive models and methodologies; their expertise presents an intriguing opportunity for application in the H&S domain. Insurance companies are fundamentally risk management entities that simultaneously seek to influence business behaviour while gathering critical information about operational practices. Their primary financial concerns revolve around claims payouts and workers’ lost time. Accident frequency distributions and company size data provide essential risk and volume indicators.

Insurance is a commercial mechanism designed to minimise potential losses. Actuaries are responsible for computing insurance rates and their studies are particularly crucial when insurance companies are viewed as reputable financial institutions. H&S considerations are critical in the actuarial profession; for example, they can recognise long-term injuries.

With extensive H&S incident data at our disposal, imagine the potential of collaborative efforts between H&S professionals and actuaries to develop a predictive model for workplace accidents. Such a model could account for industry type, workforce size, and employee skill levels.

Developing a predictive model for occupational accidents typically involves identifying, constructing, and iteratively refining various statistical and machine learning approaches. Comprehensive statistical techniques from social science are essential for analysing and modelling accident probability. Supplementing H&S statistics with relevant case studies provides additional depth. Globally, the primary causes for accidents include being struck by objects, falls from height, slips, and impact incidents.

The actuarial profession’s protocols involve generating complex numerical and financial analyses. Leveraging actuarial science, we propose a nested algorithmic approach that applies rigorous online accelerated statistical methods.

Looking to the future, I believe that passionate professionals working on innovative occupational H&S models – driven by an unwavering commitment to zero harm – will fundamentally transform H&S knowledge and systems.

Spread the word

We encourage members to share the exceptional value of Saiosh membership, highlighting the benefits relative to membership fees. The next Saiosh Health and Safety Conference is scheduled for 15 August 2025 at the Century City Conference Centre in Cape Town.

We extend our heartfelt gratitude to Saiosh stakeholders for their continued support and participation. We honour and thank our members for their professionalism and dedication to creating healthier, safer workplaces that ensure workers return home safely to their families.

Health and safety regards.