Subscribe to Our Blog
My colleague at Pinnacle Actuarial Resources, Inc., Gary Wang, often says that he’s lucky. As a consulting actuary in the field of predictive analytics, Gary lives the exact life he envisioned for himself when he was a kid. I understand how Gary feels. We are fortunate to work in an exciting and expanding industry absolutely filled with opportunity. We get to work with great clients and tackle interesting projects on a daily basis. It’s an exceptional time to be in predictive analytics and I agree with Gary: We are incredibly lucky.
There is a phrase that I hear often lately: “Luck is when preparation meets opportunity.” It’s a phrase that resonates for me. Students and new analysts sometimes ask me how I became a predictive analytics practitioner and if I might have advice to help them get more involved in the field. Is it possible for me to say that I just got lucky? While that may be true, my good luck isn’t the most helpful roadmap for any aspiring analyst or actuary.
If luck (alone) isn’t the greatest answer, how does a young actuary or analyst find opportunity in predictive analytics?
I believe there are things that can be done and steps taken to prepare for and take advantage of opportunities (and luck) to work and succeed in this tremendously exciting field.
Preparation / prepəˈrāSH(ə)n/ – noun, the action or process of making ready or being made ready for use or consideration.
Today, there are more tools than ever to help train actuaries in predictive analytics.
Early in my career, I was told that it was prudent for actuaries to learn how to program and code. You can’t or shouldn’t wait around for IT to provide data, the thinking went. That adage has proven true throughout my career. Whether you are pulling data for rate indications, reserve analyses, ad hoc reports, or full-blown analytics projects, you often have opportunities in your day-to-day work to develop programming skills. Skills that I believe are vital to successful predictive analytics projects.
There are other avenues for learning aside from the skills analysts may pick up in the course of day-to-day work. The CAS Institute’s (iCAS) Certified Specialist in Predictive Analytics (CSPA) credential provides great preparation for performing predictive analytics. The CSPA curriculum combines insurance fundamentals, data concepts and predictive modeling techniques with a case study project. I encourage anyone interested in predictive analytics to explore the CSPA. Even if one does not choose to obtain the credential, the path itself can serve as a blueprint for self-study to ensure well-rounded coverage of skills and knowledge. More information about the CSPA credential can be found on the organization’s website.
The Casualty Actuarial Society (CAS) also recognizes the importance of predictive analytics skills for actuaries, and has been proactive in providing training opportunities in the R and Python programming languages. There also exists other, more creative opportunities to develop predictive analytics skills. As examples, one could participate in a company-sponsored Lean Six Sigma project, volunteer on a CAS research and development committee or even simply explore datasets on Kaggle. (You may want to start with seeing if you could have predicted the movie character Jack’s demise on the actual Titanic.)
Opportunity / äpərˈt(y)o͞onədē/ – noun, a set of circumstances that makes it possible to do something.
It is more difficult to design a roadmap for opportunity. One can’t predict (sorry!) where and when the opportunity to get into predictive analytics might come. It may be hard to wait for an organic opportunity. Are there ways for professionals to put themselves in a position to create opportunities?
The answer, once again, is preparation. I believe the more you prepare, the more opportunities arise. That is preparation meeting opportunity. It is when:
Preparing for, recognizing and acting on an opportunity creates luck in predictive analytics and everything you do. The opportunity may not always look perfect. But always be ready: According to the song “Timing is Everything,” sometimes “the stars line up, you catch a break and people think you’re lucky.”
*Lean Six Sigma projects that measure the cost benefit of improving processes that are producing substandard products or services.
Special thanks to Gary Wang, FCAS, MAAA, CSPA, for his contributions to this blog.
Michael Chen is a Consulting Actuary with Pinnacle Actuarial Resources, Inc. in Des Moines, Iowa and has 14 years of actuarial experience in the property/casualty insurance industry. He has considerable experience in predictive analytics, ratemaking for private passenger automobile, homeowners and commercial insurance, as well as reserving, reinsurance pricing and catastrophe modeling. Michael currently serves as a member of the CAS Examination Committee and the Committee on Professionalism Education. He is a Fellow of the Casualty Actuarial Society, a Member of the American Academy of Actuaries and a Certified Specialist in Predictive Analytics.
« Back to Blog