Photograph: Meghann Prouse
How are you using predictive analytics in your job?
I use predictive analytics as a tool to study policyholder behavior and other insurance-related experience to help inform business expectations and decisions. Two examples include when variable annuity (VA) policyholders start utilizing a guaranteed lifetime withdrawal benefit (GLWB) rider and how different underwriting questions lead to differences in mortality experience.
Our team may use a different analytical strategy for each project. For an industry experience analysis, we may use a relatively simple model. Alternatively, with an industry-sized data set, we’re likely to have the quantity of data needed for a much more complex model, so we may opt to use machine learning and model explainers to gain further insights, accepting the impact on implementation. Overall, we try to show how new analytical methods can be an improvement over those that have sustained us to date.
How do you define success?
Success in my job is somewhat hard to define because it’s not one concluding event. When you look at the world beyond the insurance industry, it’s clear that:
- We have a lot further to go with the adoption of predictive analytics.
- Many more aspects of actuarial work can be improved by using predictive analytics.
Our job is to keep moving the bar. Sometimes that means taking a side-step to focus on improving how the results of predictive analytics efforts are absorbed by stakeholders through visualization tools. Anything we can do to increase the understanding of what can be accomplished with analytics helps the industry move forward. So I’d say success for me and my team is about whether we feel good enough about what we have done and what we are doing that we keep going, looking for what is next.
How important is teamwork in the workplace?
There are a lot of pieces that need to go right in order for us to complete our work, and no one person could accomplish all of them. We must function as a team, which involves being aware of other team members’ work, offering help when needed and trusting other team members. And, of course, work is a lot more fun as a team.
What skills positioned you for work in predictive analytics?
The hard skills that positioned me for work in predictive analytics were statistics, programming in R, visualization techniques and the business understanding I gained earning my FSA. More and more, our team also needs to have skills in data management and computing, but those are not areas that I’ve continued to develop personally.
As a principal, I find there are other skills that help me do my job. Being able to communicate with both technical and nontechnical audiences and anticipate the questions and concerns important to each audience has been very helpful. Leadership is another important skill for people at all levels. One of the most critical roles of any leader is having a vision, honing it and communicating it to your team and stakeholders.
What is the most challenging aspect of your work?
Balance. A couple of weeks ago, it was probably about 9 p.m. on a Tuesday, and I stopped on my way home from work at my local Irish pub. I wasn’t going to be able to get home, cook dinner, eat dinner, do the dishes and have time to edit the paper I was working on. So I stopped and I had them cook me dinner, and I read through the paper while I was eating. As I was finishing the last few edits, an older gentleman stopped by on his way out the door and asked what I was doing. I told him I was editing a paper, and he asked what it was about and what I did. When I told him I was an actuary and that the paper was some research my team was working on, he said: “Oh, an actuary! It’s been in the paper the last few years. You have the best work-life balance.” I think I smiled and said, “I must not be doing it right.” I hope I’ll improve, but I don’t expect the struggle to go away while I stay in this line of work—there are so many more interesting things I could do with just a little more time. I know at least a few members of my team feel the same way.
So not only is prioritizing for our team challenging, it’s also tough when something interesting we could do doesn’t make the cut, especially when it’s something that is a passion of one of our team members. I would say that’s the most challenging aspect of my work.
As a member of the Society of Actuaries (SOA), why do you volunteer?
I believe it is important to foster community among actuaries involved in predictive analytics. A great thing about volunteering is that I have more opportunities to help the industry do just that. As chair of the Predictive Analytics and Futurism Section, I attend meetings with the broader volunteer group, discuss ideas with people who can make them happen, and meet leaders of other sections to find ways to collaborate. As section chair, I also have the opportunity to set our research direction. My main hope is that we can create a place where actuaries know they can go to find information on cutting-edge techniques and the best practices for implementing them. I believe building a strong community within our section will help that happen.
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