Every CAS president has the opportunity to share a president’s message in each issue of the Actuarial Review. While many presidents have used this space to share their insight on current events or deep dives on the profession, I’m trying something different. For my president’s messages, I’ll share interviews with actuaries who embody our new Envisioned Future, which says: “CAS members are sought after globally for their insights and ability to apply analytics to solve insurance and risk management problems.”
For the first interview, I talked to Frank Chang, Head of Safety and Insurance Analytics at Uber. Frank found his way to the actuarial profession by following insurance stocks for The Motley Fool. He traded piano lessons so he could study for his first two actuarial exams and taught himself Python at age 40.
Below is a brief excerpt of our engaging and revealing conversation. For more, see my column in the January-February issue of Actuarial Review and watch the video at AR Web Exclusives.
Jessica Leong: If I’m sitting in an Uber, what would I notice that you and your team have done to make my ride safer?
Frank Chang: A lot of the safety features. So, for example, the safety center that you see in the app that you can find at the bottom, the SOS button that’s in the safety center and a few of the newer features we’ve launched. Some rides actually have a PIN confirmation where you can make sure that you have the right driver. For COVID, there are photos with mask detection to see if folks are wearing their masks, which is required in all Ubers.
JL: You made your way up from director of actuarial services to the head of safety and insurance analytics at Uber. How did you manage to take on bigger and bigger roles?
FC: You have to be intellectually curious … I’ve said this before to other actuaries. The actuarial exams are a good preparation for a wide variety of subjects. We could always ask, “Why do we need to learn regulation on our exams?” But if you dig into that, you then become an insurance professional. When you leave an insurance company, folks don’t really understand insurance.
Both the insurance and data science aspects of my knowledge base improved because folks were asking, “Can you solve this?” and “Can you solve that?” You have the competitive advantage here. From that I was able to get into Uber … Insurance and safety merged, and I was able to credibly talk about safety. We deal with rare events all the time [as actuaries]. Not very many data scientists out there are used to it. They don’t know the difference in errors. They don’t have the thought of how to cut your data, so you have homogeneity and credibility at the same time.
