AI in the actuarial skillset - Interview with Sarah Schadek-Keane

Artificial intelligence or machine learning is one of the hot topics in most professions and working environments in general. For actuaries’ analytical and prognostic tasks, however, AI has an even higher significance than in most other fields, not least because coding is an integral part of the skillset for many actuaries. How do you assess the development of machine learning and artificial intelligence in the past three years for the actuarial profession?

I think the biggest impact has been the exponential growth of data and how AI processes this huge amount of data and learns how to accomplish tasks that had previously been done by employers. It has also become more relevant for the healthcare sector, and is likely to become a standard tool for doctors and physicians supporting their diagnostic work. The transportation sector has also seen changes which are highly relevant for the assessment of risks within the insurance industry, such as driverless cars or other autonomous vehicles.

What are the advantages due to the increased attention and rapid progress for actuaries in their professional environment?

I think it opens the actuarial profession to broader and more data-focused roles. It will increase the pace of how roles will change. From what I’m seeing with Emerald Group clients actuaries will need to be more flexible and adjust their roles to the demands of new tasks and evaluations. Actuaries will need to team-up with AI-processes and applications to take advantage of these technologies, so programming skills will become more relevant.

How can be knowledge and qualifications in dealing with AI be made visible in the actuarial skillset? And how can employers be convinced of the advantages? 

Knwoledge and qualifications around creating new tools and applications are important to show how to use the large amount of data they captured in a global environment. Actuaries also need to demonstrate a critical mindset and strong analytical skills to assess and manipulate outcomes - a skill more crucial now than ever before. Embracing life-long learning is likely to become more signifcant due to additional qualifications (such as CADS) that will merge around this topic. It’s also important to raise awareness of the risks that AI brings to the table including the above areas of health and transportation - as wells as the regulatory framework within companies, be they local or global.

According to your experience, which knowledge and skills are currently in particular demand in this context – and which ones could be in the future?

Programming skills in Python or R, domain expertise, and other skills on how to extract insights from data, which translate into business value (e.g. market intelligence, risk assessment etc.) are important to organizations currently. When talking to candidates at Emerald Group, the mistake some actuaries currently make is that they think that this is a strategic topic, whereas currently this is more of a hands-on job. This means improving algorithms and systems to extract data for insights as well as processing a broad range of data sets to create valued insights on a topic, as well as recognizing patterns and making informed forecasts about risk probabilities. In my work with client and candidates, I’m seeing a great deal of interest in AI and machine learning. There are tremendous opportunities both for businesses and actuaries here, specifically for people who build skills and knowledge in this area.

For specific insights on Artificial Intelligence in Job Interviews, read this article in Emerald Group's News Blog.