Why Actuaries shouldn't fear Data Scientists

As the Data Science hype has risen, Actuaries have staked a claim that they are the original Data Scientists. It's true, Actuaries have been developing mortality tables and calculating future net premiums since the 1800's, but in today's age it often seems like the profession is still stuck in the past century.

The reality is there hasn't been much innovation in the techniques used to predict risk in decades. The profession seems like it is more concerned with keeping the barriers of entry high through a prolonged certification process instead of training for the skills actually needed to be the most efficient on the job. And let's be honest, if you are a bright high school student choosing a career path, working for FAANG sounds far more appealing than being employed by the big insurers.

The Actuarial brand is closer to a bunch of math-obsessed, socially disconnected individuals with shockingly bad comb-overs rather than the Sexiest Job of the 21st Century. The challenge to stay relevant in the industry is so real, even the Society of Actuaries has acknowledged more needs to be done.

So why is it not all doom and gloom for the Actuaries? Well, they certainly can't afford to take a reactive approach there are several key areas where the Actuaries have a unique advantage.

Subject Matter Expertise

One of the fundamental aspects of being an Actuary is having an understanding of your domain. Whether that is life and annuities products, investments and financial engineering or general insurance, having a financial underpinning is what allows Actuaries to intricately understand how various forms of risk can impact the income statement. Traditionally, data scientists have not been exposed to finance and insurance use cases as much as ones in sales and marketing, but they will all tell you that having that domain expertise can not only accelerate the development of a solution but can help avoid the team from making crucial errors as well.

Statistical Prowess

Having gone through a rigorous certification process, an Actuary can understand the statistical nature of the modeling techniques with relative ease. They already have the necessary prerequisites of linear algebra, differential equations, distributions and much more. Having this deep mathematical understanding allows them to interpret what the algorithms are doing under the hood and be able to communicate with more than just the jargon. Technology will keep on revolutionizing our industry, with more sophisticated algorithms and unique approaches. With thousands and hours of self learning under their belt, an Actuary is well equipped to have the discipline and motivation to stay up to date on the latest developments.

Ethically Driven

As we have evolved into a more data driven society, we have seen the largest tech giants wrestle with safe storage and ethical usage of the vast amounts of personal data they capture. This is not a simple job but Actuaries have professional obligations to uphold the reputation of the actuarial profession and fulfill the responsibility to the public, a big part of which involves cooperating with regulators, auditors and other stakeholders. Actuaries are required to adhere to the Code of Professional Conduct and Actuarial Standards of Practice which help guide them in making important data decisions.

The Actuary and Data Scientist are unique in their own ways. Where one lacks, the other flourishes leading to learning opportunities for both professions. Being actively employed as a non-traditional Actuary in Data Science, I am biased but I really believe Data Science has the potential to make a significant contribution to the finance and insurance industries. It's our choice to fear the change, or lead the charge.