SPOTLIGHT ON DOROTHY ANDREWS: A NON-TRADITIONAL CAREER PATH

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It’s always a pleasure speaking with Dorothy Andrews, an inspiring actuary who I have known for 20 years! She is extremely sharp, has a great sense of humor, an infectious laugh, and the ability to explain technical concepts to a non-technical audience (which includes me). You may know her from her many presentations at industry meetings or articles in industry publications covering a variety of topics, including – Media Psychology, Bias in Data and AI, Rate Models, Mitigating Bias, Predictive Analytics, and Bias in AI.

Thank you, Dorothy, for taking time out of your schedule to answer these questions. Your path as an actuary is an inspiration!

What inspired you to pursue a career in actuarial science, and how did you find yourself on a non-traditional path?

I learned of the actuarial profession while I was doing graduate work in mathematical statistics at Boston University. After doing some research, I felt the actuarial profession would allow me to apply my statistical background to solve real-world problems. In my first position in pursuit of an actuarial career, I applied my knowledge of statistics to build a capital asset pricing model (CAP-M) that could be applied to mutual insurance companies. This was a very challenging theoretical exercise because mutual companies don’t have an observable measure of risk that is equivalent to risk measures for publicly traded insurance companies. This project convinced me that I wanted a career as an actuary.

Can you share a specific experience or project that highlights your unconventional career trajectory?

During my tenure at John Hancock Mutual Life Insurance Company, I was always attracted to projects requiring statistical and data analytics skills. I enjoyed working with information technology (IT) professionals to help them interpret the actuarial content of actuarial projects so they could correctly program actuarial solutions. During this time, I learned a lot about IT architectures and protocols. I found a common language with IT professionals, and I learned to appreciate them for their talents as much as they appreciated my ability to translate actuarial project requirements into terms they could understand.

What skills from your non-traditional experiences have been most valuable in your actuarial work?

Without question, you need strong theoretical statistical skills. A modeler needs to be able to distinguish between statistical noise and true statistical signal in underlying data. A modeler needs strong data modeling skills, which requires an ability to understand when statistical results fail to replicate significant business relationships.

Being able to work with an interdisciplinary team of professionals is also a must, and this requires strong communication, interpersonal, and interviewing skills. It is often the case that people do not understand how what they know can be helpful to others. Modelers with little background knowledge of a business can use developmental questioning techniques to determine whether important business relationships are patterned in modeling data and research causes when those patterns are not present. The requisite communication style needs to give people a sense of inclusion in building predictive models to maximize the utility of the business experience of other team members. To work in this area, a modeler needs strong statistical, data mining, and modeling skills, developmental questioning skills, and an inclusive communication style—because models don’t build themselves, people do!

How do you think the actuarial profession views non-traditional paths, and what changes would you like to see in this perception?

I think the actuarial profession is still focused on traditional pathways and is not as focused on some of the more novel ways that actuaries can find utility in other fields. I think some of that is due to the nature of the exams. The exams are very much focused on traditional risk topics and not every industry is focused purely on technical insurance matters. However, data science is opening other career pathways for actuaries. For example, you see actuaries going to work for InsurTech companies, banking and finance companies, and software companies. It is important for actuaries to think about how their skills transfer to other areas where they may have interests. When I worked for Wachovia, I worked in its credit risk management department. I found my skills with mortality tables were directly transferable to studying the default patterns of loans. When a loan is granted, it can take one of two paths, complete repayment or default. That is very similar to the journey of a life insurance policy once it’s issued. It either lapses, results in a death benefit, or reaches maturity.

I would like to see the actuarial member organizations start promoting actuaries in other fields. Such efforts will grow the profession and expand our presence in fields that would benefit from our deep analytical skills.

What advice would you give to aspiring actuaries considering a non-traditional career path?

I think my advice to any actuary or anyone on their career journey is to find something you really like doing and figure out how your skills can make you an asset. Actuaries have a great advantage when considering non-traditional roles, which is that they are highly regarded as very smart people. However, they need to work on their interpersonal and communication skills. It is very important to be able to communicate technical material in very simple terms. This may sound obvious to many people, but it is a very important skill in gaining trust and access to upper management, and even becoming upper management. When people understand your explanations of complicated material, they will come to trust you and you will become their “go-to” person for information important for decision-making. It is important to be engaging as well, which is often difficult for actuaries, myself included. We have a “comfort zone,” which prefers the few to the many.

Have you collaborated with professionals from other fields? How did that shape your approach to actuarial problems?

There is no doubt that actuaries can benefit from collaborating with others in different fields. I have always found that as much as I know, I am still learning how much there is to know. It is important to get other viewpoints on issues and be open to other approaches. This allows for non-routine problem-solving approaches which are the breeding grounds for creativity. Diversity of thought is also important because actuaries have been trained in methods that have been used since the beginning of the profession. Engaging others from different fields can open actuaries up to brand new ways of thinking about problems and discovering how their skills can be assets in solving them. Some of my greatest collaborations have been with social scientists and the use of qualitative methods.

How do you stay updated on industry trends and developments, especially given your unique background?

I stay involved through volunteerism. I volunteer with the SOA and the AAA. I chair the AAA’s Data Science and Analytics Committee (DSAC) and was its first chair. In that role, I have led the development of several technical papers that have had cross-practice participation. As a result, I am involved with P&C, Health, and Life issues and I ensure the technical papers the DSAC authors apply to those practice areas. I have been a lifelong volunteer with the SOA and their research and education efforts and continue to volunteer on project oversight groups involving artificial intelligence related topics. I am currently an SOA delegate for the International Actuarial Association (IAA) working with a global team of actuaries to examine AI governance frameworks around the world. I am also connected with data scientists through meetups and civil rights AI auditing groups. It is not hard to keep up if you volunteer. Volunteerism is a great way to keep up on current insurance and regulatory issues and contribute to the profession. I also work for the NAIC on regulatory issues that affect life, health, and P&C.

How has your non-traditional path influenced your long-term career goals and aspirations?

My technical skills have been enhanced by getting a PhD in media psychology. Most people think of media as print, radio, and TV, but it also includes big data and algorithms. When both these media became relevant for insurance, I became concerned with the potential for big data and algorithms to alter our perceptions of risk. This has direct implications for insurance. We are currently witnessing increasing mediation of insurance with the use of mobile, wearable, and other AI technologies, much of it without critical human oversight to ensure these technologies are operating ethically and with transparency. These technologies, especially automated decision-making systems, often have disparate and adverse impacts on those segments of society who lack the privilege and resources to avert their ill-effects. This is my primary motivation for working in the regulatory realm. I can use my skills to help ensure the responsible and ethical use of AI, without stifling its innovative use in insurance.

How can the actuarial profession evolve to embrace non-traditional pathways in the future?

Promotion! Promotion! Promotion!

Who or what was a significant influence on your decision to take a non-traditional route, and why?

I am a naturally curious person with lots of interests. While my journey has not been without struggle and difficulties, I do believe all my experiences have brought me a lot of clarity around how to spend the rest of my career.

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