Photograph: Joel Maisonet
How does technology growth affect actuaries and the profession?
Technology growth affects actuaries in several basic ways. Technological advances change what we are able to accomplish and determine the expectations others have of us. Without advances in technology, many of the approaches to stochastic analysis would not be practical. Technology has changed the expectation of the depth and speed of our analysis, and the latest advances are changing how we communicate. I often ask actuaries when the last time they used a “heat map” to communicate a result was. As actuaries, we tend to provide “the” answer. We have the most powerful tool—a smartphone—in our pockets. We have information at our fingertips via the internet. So we are being conditioned to process information differently. We do not want the answer—we want the information to make our own informed decisions.
There is a growing body of research on the way technology is changing how we process information. Processing power changes what we can accomplish and what is expected of actuaries. I recall when it took several days to perform various cash flow scenarios. These same calculations now can be performed in hours and, by utilizing distributed processing, one can accomplish tasks in minutes. Expectations of regulators, executives and other stakeholders have changed with increasing processing power.
Technology determines the skills actuaries need. Because information is readily available, the actuary is increasingly required to “make sense” of the results rather than spending significant effort compiling results. This change requires actuaries to be able to think and communicate differently. I find this confluence to be fairly unique to the actuarial profession. Namely, actuaries must understand the technical details and communicate the meaning and implications of those details to nontechnical colleagues. Our examination and continuing education requirements do an excellent job of leading actuaries down this path.
What about technology inspires and interests you?
I have always been interested in technology. I subscribed to Popular Mechanics magazine as a young child. I graduated to Scientific American magazine when in middle school. At the same time, my older brother introduced me to programming. He was an engineering student at Cornell University. Somehow he got his hands on an Apple II Plus that came with three computer compilers: one for Basic, Fortran and Pascal. During that summer, I pretty much replicated the projects he was assigned during the previous semester. By the time I was in the tenth grade, I was very proficient. I landed a job at the Environmental Protection Agency through a program for inner-city youth. Once they learned of my programming proficiency, I began working with their co-op students, designing programs to monitor the various experiments of my research group. Because of my utility, they had me working part time during the rest of my high school years. While attending college at the Massachusetts Institute of Technology (MIT), I was introduced to the hacker community. I am very social, so I enjoyed learning about the various interests of the group members. From robotics to cognitive research, each individual sparked a desire in me to have a basic understanding of his or her particular interest.
What skills positioned you for work in technology and predictive analytics?
When most people think of “skills,” they are referring to one’s ability to do something. While I accept that definition, I actually understand the question differently. My ability to accomplish a task depends upon my aptitude (not knowledge), disposition/temperament and character.
I think the most important skills seem to be universal among us technocrats:
- We tend to question everything. “Why” is by far my favorite word.
- Simple things fascinate us.
- We love to take on “impossible” challenges.
- We see problems from as many perspectives as possible.
I naturally assimilate—I take in information, ideas and concepts, and seek to fully understand them. I love to learn, but I live to understand.
I spend much of my time reviewing research on technology, invention and innovation. I also read biographies of the great thinkers and inventors. There are definite patterns. I believe there are skills that have a direct correlation with the way in which innovators think and operate. The five basic skills are:
- Being curious with a desire to gain understanding
- The ability to associate and assimilate information and concepts
- A keen power of observation
- A desire to experiment to refine understanding
- Ability to communicate, coach or teach
These are all skills that will never become obsolete or irrelevant, but are vital for understanding how predictive and data analytics can be applied to answer specific challenges. These skills allowed me to find meaningful insights in the data analysis projects I undertook. From my first assignment in outcome-based education, to analyzing political data and market research, to a more recent advisory role in analyzing mortgage delinquency data, my ability to ask the right questions and communicate meaningful insights from the analysis continues to earn referrals.
Why did you become an actuary?
I became an actuary by accident. I planned to be a physicist specializing in traffic flow. After graduating from MIT with a bachelor’s degree in math, I intended to take three years off before pursuing a graduate degree in physics. I applied for jobs as a statistician and programmer. One of the companies at which I applied was an insurance company. The hiring manager suggested that someone with my background could be an actuary and the programming positions would not be available for a few months. I took a basic test and was hired. However, because the actuaries knew of my programming interest, many assignments that involved working with our IT department or programming came my way. The company also had a tremendous actuarial rotation program.
By the time my wife completed law school and passed the bar, I loved actuarial work too much to do anything else. But most important, I found meaning in what I did. My mother passed away in the fall of 1991. I remember my father, after making final arrangements at the funeral home, commenting how he had always expected to go first, that losing my mother was very difficult, but at least he did not need to worry about the finances. I saw firsthand the tremendous value of life insurance. From that moment, being an actuary changed from being a job to being my career and profession.
Do you have any advice for younger actuaries?
I have been privileged to work with numerous actuarial interns and to speak to many college students. I always give the same advice.
- Practice great customer service.
- Tackle the exams when you are young and most likely have fewer family and job responsibilities.
- Learn the disciplines of programming. Structured languages, such as Pascal or C, or even Basic, are best. Gain a working knowledge of R.
- Learn to communicate complex issues in simple terms. Being a technician has limited career potential.
How are you using predictive analytics in your job?
My current role does not lend itself to employing predictive analytics. Most of my experience has been as a consultant or in an advisory role not related to insurance. In addition, there is a subtle difference between predictive analytics and data analytics. I try to help individuals determine whether “prediction” or “insight” is desired. Market research is primarily “insight” driven. The effectiveness of various marketing campaigns can be “predictive.” I have worked on both types of challenges. The questions you answer are vastly different depending upon which of the two approaches you use.
My very first project analyzed data from four different public school systems. The objective was to recommend the best uses of limited dollars to reduce the number of students that ultimately enter juvenile courts or experience incidents with the police. We followed students’ experiences over 10 years. Based on the data, the recommendation was to spend additional dollars targeting students who were in danger of failing a grade prior to fourth grade. Of all the measures and instruments we utilized, this by far was the greatest predictor. When testing this recommendation, there was an observable difference in outcomes when comparing the general student population against students participating in a particular program.
Property and casualty and health insurance have made the best inroads in gaining insight through predictive analytics. I think there is great potential for life, disability and annuity products. Understanding the two types of analytics will clarify the promise of analytics. For example, understanding which aspects of life insurance are predictive by nature will help individuals think of applications of predictive analytics. Underwriting is predictive. Although not as obvious, morbidity, policyholder behavior, sales results and persistency also can be predictive.
From my perspective, data analytics has more potential. For example, I spoke to a particular agent who was able to define what he called his “sweet spot” for sales. He gave a particular age, income range and reason for purchasing life insurance (namely, someone wanting to increase net worth). The questions raised in my mind were how many different categories of “sweet spots” do our most successful agents employ, and are we designing products to maximize sales and profit? Do we want this business? Do we have monitors in place to alert us to changes in policyholder behavior? Do we track the perceived needs of our policyholders or the marketing concept that led to the sale? How are we reporting utilization of various calculators and reports, or monitoring web traffic?
What is your dream job?
My dream job would be to be given a city and challenged to recommend and implement interventions to improve the health of the various communities and neighborhoods. I spend much of my time developing concepts and theories around the challenge of urban renewal. I spent more than nine years volunteering and serving on the board of a local ministry. On a small scale, I observed successful and failed programs and projects. I drew upon my own childhood experiences, research studies and discussions with various community leaders. I developed a theory that there are seven basic pillars to a healthy society:
- Community investment/homeownership
My dream job would be to lead a collaborative effort to demonstrate how to rebuild the foundations of one of our many failing urban centers. In the meantime, I am content to play my small part.
Copyright © 2018 by the Society of Actuaries, Schaumburg, Illinois.