New Actuaries Must Know About Machine Learning—Audio Version
New Actuaries Must Know About Machine Learning has turned out to be one of my most read articles, with over 1,100 views across the platforms it’s been published on at the time of writing. I imagine it’s because there isn’t a huge number of young professionals who have had the opportunity to study under the Institute and Faculty of Actuaries’ new 2019 syllabus yet.
Having just studied subject CS2, which was adapted to include content on machine learning, I wanted to share my thoughts on how well the syllabus changes have addressed the deficiencies that the IFoA had identified in the old material. Essentially, my verdict was that the new material serves as a well-rounded introduction to the field—although as someone who was keen to go further and work on some end-to-end projects in an actuarial context, I was initially a bit disappointed that there wasn’t any actual coding required. However, I eventually came to terms with the fact that this new material was only really intended to introduce the field of machine learning and to help students develop a level of familiarity with the various techniques.
I would like to see more from the IFoA in terms of study material and projects with which students can properly “get their hands dirty” with machine learning in Python or R. Nevertheless, I am filled with optimism as a result of the profession taking the first step (hopefully with several more to follow) towards preparing its newest members to serve the ever-changing needs of their clients—because for actuaries working with data, the future has already arrived.