Actuarial science, the backbone of insurance and financial risk assessment, has stood the test of time by continuously adapting to new technologies and methodologies. The incorporation of artificial intelligence (AI) – including machine learning and data analytics – into actuarial practices marks a significant leap forward, promising to revolutionize how actuaries predict risks, model scenarios and devise insurance policies.
However, the rise of advanced AI also introduces new challenges and uncertainties. The same tools that empower actuaries to refine their predictions can also obscure the transparency of risk models, leading to complexities in understanding and managing the models’ outputs. Moreover, the increasing sophistication of AI could potentially disrupt traditional actuarial roles, necessitating a reevaluation of the skills and knowledge required in the field. As the actuarial profession navigates this transformative era, it is crucial for its practitioners to remain vigilant and adaptable to the evolving landscape. That way, they can ensure that AI serves as a complement to, rather than a replacement for, the nuanced judgment and expertise that have long defined actuarial science.
In this article, we explore seven questions for actuaries operating in an increasingly AI-enhanced world.
1. Which aspects of the traditional actuarial function will be most impacted as AI evolves?
Actuaries can expect a profound shift, requiring them to redefine the profession. Multiple aspects will be affected, including capabilities, activities, services and interaction with others.
Actuaries in the future will need to have enhanced analytical capabilities. AI will help actuaries process and analyze vast datasets more efficiently than before, providing users with deeper insights and the ability to tackle more complex problems. AI will also enable increased automation of the numerous manual and repetitive tasks that actuaries currently still perform every day.
2. How can actuaries remain relevant in an AI world?
Actuaries will need to adapt and integrate new skills into their repertoire. This includes understanding and leveraging AI and machine learning technologies to enhance their analytical capabilities. Developing skills in programming, data science, and AI ethics can also be crucial. Furthermore, focusing on areas where human judgment and contextual understanding are paramount – such as strategic decision-making, ethical considerations, and personalized customer service – can ensure actuaries continue to add significant value beyond what AI can provide.
3. Will this impact new profiles and recruiting in insurance companies?
The integration of AI in insurance companies will lead to a shift in the profiles and skills sought after in new recruits. There will be growing demand for candidates with a blend of traditional actuarial skills and expertise in data analytics/AI. Soft skills will also becoming increasingly important as companies may look for individuals who are adaptable, continuous learners and capable of working effectively at the intersection of technology and business. This evolution will likely lead to more interdisciplinary teams combining actuarial science with data science and computer programming roles.
4. If AI knows all the actuarial techniques and calculation methods, do actuaries still need to study mathematics and statistics?
Yes, proficiency in mathematics and statistics remains essential. Understanding the underlying principles of these disciplines is crucial for designing, interpreting, and validating AI models and algorithms. Actuaries need these skills to ensure models are accurate, reliable, and ethical. Moreover, a strong foundation in mathematics and statistics allows actuaries to critically assess AI outputs and make informed decisions, ensuring that human insight and ethical considerations guide the use of technology.
