Fabian Beiner created a website that classifies races that have the potential to be replaced by a robot. He calculated that actuaries have a 21% chance of fully automating themselves and that “they will almost certainly not be replaced by robots.” Actuaries are much more likely to be replaced by other humans than by robots in the near future. Think of the progressive strategy of reducing actuarial staff to only basic legal requirements and replacing them with cheaper data scientists and analysts. Actuaries are there to set up the calculations, verify that they make sense, and interpret the results.
Insurers must automate a significant amount of the actuarial workflow to keep up with demand, reduce costs, and properly utilize existing actuarial resources. Surprisingly, I think that data scientists working at the applied end of the spectrum are more likely to be replaced by robots rather than by actuaries. While most actuaries aren't complete programmers, most of us know at least enough to do a few loops in VBA. Most actuaries don't even have access to the right data, so they need to design their own models and processes.
It's no secret that one of the main causes of pressure on insurers' actuarial resources are legacy systems and processes that require much of their time and attention. Many, if not all, of today's actuaries will argue that this can never happen because the trial is too critical. However, the demand for calculations has kept pace with their availability, so I continue to imagine the need for actuarial students or data scientists. This is because, despite automation, actuarial judgment continues to be applied at every step of the process, whether in the manipulation of data, the establishment of hypotheses or the selection of methodologies (mainly for the reservation of non-life insurance).
According to the Bureau of Labor Statistics, average salaries for the three professions fall within a similar range, and starting salaries for data science and computer science jobs are rising rapidly than those for beginning actuaries. The emergence and growth of lucrative and flexible careers in data science and computer science offer attractive alternatives for many people who traditionally would have pursued an actuarial career. In addition to striving to get the job done, junior actuaries who spend less time on their duties force senior actuaries to take on junior level jobs. AI provides the actuarial profession with a structured, coherent and impartial way of performing actuarial work that minimizes the need for human intervention.
On top of that, regulations are constantly changing, products are constantly changing, times are always changing, and actuaries must be able to effectively design products to keep up to date. These competitive career paths, together with an estimated 24% increase in demand for actuaries, are a serious problem for insurers, particularly in the life and health insurance industries. The increase in visa restrictions and the emergence of equally attractive jobs in similar fields, such as data science and computer science, mean that insurers are already struggling to find the actuaries they need to do their jobs.
