Actuarial capabilities—a mix of quantitative skills, product knowledge, and understanding of regulatory requirements—are indispensable in insurance. The industry is handling more data, using more advanced techniques, making faster decisions, and sometimes facing greater uncertainty. The COVID-19 pandemic has also accelerated the already underway shift to digital channels, including a renewed appreciation for algorithmic underwriting.1 In step with rapid technological changes and ongoing adoption of advanced analytics and artificial intelligence (AI), actuaries will need to change as well.
Greg Heidrich is the executive director of the Society of Actuaries (SOA), the world’s largest professional organization for actuaries, with 31,000 members. The SOA oversees the approximately eight-year journey through which actuaries are certified to become Fellows of the Society of Actuaries. In this interview, Greg discusses the role of actuaries and data scientists and how it might change. He also describes how the actuarial role may evolve as it incorporates new technology and helps the industry face new challenges.
McKinsey: How would you describe the role of an actuary in a typical insurance company?
Greg Heidrich: Actuaries have been around for as long as there have been insurance companies. Actuaries have been called the “brains of the insurance business” because they use mathematics and statistics to estimate the financial impact of risk and uncertainty and better manage risks. They work on product design and development, pricing, reserving,2 financial reporting, solvency testing, regulatory compliance, and R&D. Actuaries focus on enterprise risk and often view themselves as risk managers, first and foremost. They now increasingly work on data analytics and big data projects
McKinsey: How is the actuarial role changing in light of advances in technology and analytics?
Greg Heidrich: What actuaries work on, what management expects from them, and how the work is done are all changing. First, a lot of actuarial processes are being partially to fully automated and scattered to many parts of the world. The SOA is not directly involved in those efforts, but we do hear from our members that this trend will continue. Second, insurers everywhere are moving into big data and analytics as fast as they can. Companies are adding staff dedicated to advanced analytics, and these new teams often include data scientists or other professionals who are new to the insurance industry. At the SOA, we train our members in the techniques of data analytics to provide value and leadership in these new organizations. We believe actuaries can make unique contributions with their quantitative background and understanding of insurance fundamentals.
Finally, we see the need for more soft skills—more nimbleness and intuition—as modeling becomes more complex. Greater complexity, particularly with machine learning, makes inputs and outputs harder to understand. In this world, we need better intuition and business judgment so we can more effectively train the algorithms, challenge outputs, and translate results into actionable insights.
McKinsey: That seems counterintuitive. Do you use soft skills—or hard skills—in the world of complex models and algorithms?
Greg Heidrich: It’s one thing to set up a program and run queries against multiple data sets and look for correlations. It’s something very different to sift through the best options from a range of plausible outcomes or recommendations. That is a higher-level skill set. Actuaries bring strong insurance-specific knowledge, but they will also need to use the skills of translation, interpretation, judgment, and communication to provide real value.
One trend we watch closely is AI, which is rapidly driving down the cost of sourcing data and generating predictions. Any profession, including the actuarial profession, that tries to compete head-on with AI in the prediction business will lose. However, an actuary—or any other insurance professional, for that matter—who can effectively complement these cheaper predictions will be much more valuable. And to learn new techniques for dealing with more-complex modeling, actuaries will need to develop their flexibility and adaptability. They will need superior business judgment, especially as models become more advanced. They will also need sharp communication skills to translate output into variables that can be used in rating and pricing.
The combination of quantitative skills, insurance and regulatory knowledge, and professional standards are unique to actuaries.
McKinsey: Should actuaries or data scientists be playing this translational role? In fact, are these roles in competition?
Greg Heidrich: For a long time, actuary was the preferred profession among those with strong quantitative backgrounds, but some have observed that actuaries have been losing ground to data scientists. Many insurers’ data science teams are growing rapidly and taking on tasks that sometimes overlap with actuarial work. Today, college students increasingly view data science as an attractive career option for those with quant backgrounds.
So yes, there is competition between data science and the actuarial profession. Data scientists bring new skills, particularly programming. Sometimes data scientists are perceived as operating with fewer constraints compared with actuaries. Many young people may also see data science as a more versatile career option that offers opportunities to work across industries.
Despite these dynamics, it’s hard to see data scientists replacing actuaries. Actuaries have unique skills developed over years of training and apprenticeship that are hard to replicate. There are no shortcuts to building the understanding of insurance economics and regulation that actuaries have.
McKinsey: Can you outline some of the distinct skills that actuaries have compared to data scientists?
Greg Heidrich: Actuaries have been called the original data scientists. The profession is built on the analysis of data—mortality, experience, and claims—and has been successful in this role. Besides analytical skills, actuaries have deep training in how to combine probability theory and financial mathematics to create an insurance product that creates value for both the insurer and the insured. Actuaries also have a deep understanding of how regulatory systems work.
Another critical value of actuaries is their professional status: they are held to strict professional standards of practice that demand integrity and rigor. The combination of quantitative skills, insurance and regulatory knowledge, and professional standards are unique to actuaries.
By contrast, data scientists have deep quantitative skills, computer science knowledge, and programming experience. But there is not yet a Society of Data Scientists that requires rigorous professional standards. Data scientists can have anything from a bachelor’s degree to a PhD.
The distinction between an actuary and a data scientist may gradually disappear. Data scientists in the industry are becoming more fluent in insurance and learning some actuarial skills, especially with very large and repeatable data sets. The SOA is also updating its curriculum so certified actuaries have core data science skills. In the future, I expect most successful insurers will continue engaging both actuaries and data scientists to work in tandem, and the roles will continue to become more similar.
McKinsey: How has the COVID-19 pandemic affected the actuarial profession?
Greg Heidrich: In one word, acceleration. The COVID-19 crisis has significantly accelerated the trends that were already with us. I expect to see a faster shift to streamlined underwriting and to greater rates of digital adoption. Every part of insurance that can be automated or digitized will be. The pandemic is a call to action for insurers—and, frankly, organizations throughout the economy—to accelerate their innovation.3
At the SOA, we are accelerating our own transformation. We had already planned to make more of our educational programs and examinations digital and to make our credentialing system more modular. Now we are fast-tracking our shift to offering more microcredentials, more certificates, more digital badging, and more virtual or digital learning opportunities. For example, this year we’re converting all our learning opportunities from in-person to virtual. That means new delivery methods, new event designs, new pricing models, new attendee engagement methods—new everything. We’ve since learned that these events attract attendees never drawn before because our programming is now more convenient and less expensive. Employers and members seem to appreciate it. We’ll return to in-person learning and professional development when we can, but virtual programming is now a permanent part of what we offer.
We are also accelerating shifts in our curriculum toward skills more insurers will demand—for instance, by increasing the emphasis on nontechnical or soft skills around judgment, decision making, adaptability, and change management.
We will also change the way we test skills, starting with a new predictive analytics exam. After about six months of learning from online modules, candidates take a required five-hour exam in which they receive a business problem to solve, a set of tools such as R Studio, Excel, and Word, and a data set. It’s a simulation of the type of challenges they will face in the workplace.
One more big change for the SOA is that we are doubling down on our investment in becoming more global in our outlook and activities. The largest relative growth in insurance markets over the next decade will be from faster-growing economies in Africa, Asia, and Latin America. We want to be ready to serve actuaries—a global profession—in those areas.
McKinsey: Insurance can be a very local industry, especially when it comes to regulations. Is the actuarial profession really a global profession?
Greg Heidrich: There has always been a need for localized insurance knowledge because the industry is governed by local laws and regulations. Actuarial societies in many countries provide the local knowledge, practice standards, and regulatory context needed to practice there. In fact, the SOA partners with local actuarial societies that provide the local certifications.
At the same time, a great deal of actuarial practice is the same across the globe. For example, probability theory, financial mathematics, modeling skills, and short- and long-term liabilities will not change from one country to another. Regulators, solvency supervisors, and global insurers are also working to align international insurance regulatory systems as much as possible. As the industry shifts to working with fully digital systems, we see more opportunities for global collaboration between insurers, disciplines, and organizations like the SOA.
McKinsey: Going back to current events, how is the SOA responding to renewed societal attention on challenge of diversity and social injustice?
Greg Heidrich: The last few months have been difficult, painful, and a major wake-up call. Like most organizations, we’ve reflected on our own culture and how we can foster more diversity. Over the past few years, we have collaborated with organizations such as the International Association of Black Actuaries to do research on this challenge and explore solutions.4 We’ve not been as diverse along the lines of ethnicity, race, gender, or nationality as we should have been. In an industry that seeks to be relevant to diverse populations, we have to do more. To that end, we’ve committed to adding more diversity, inclusion, and equity efforts to our education pathway and research agenda.
McKinsey: What is your parting advice to CEOs and CHROs about how to think about actuaries within their broader talent-management strategy?
Greg Heidrich: Frankly, I think actuaries are often underappreciated, sometimes viewed as too conservative or too risk averse. Yet the actuarial profession has an important historical and regulatory mandate to defend the financial integrity of the business and to ensure solvency for the industry. It’s fundamentally a risk-management vocation.
But we see shifts in the profession, especially in younger generations. They have a real thirst to be more involved in innovation, to do socially important work, and to be part of the changes the industry and society need. And they are more tech savvy, of course. Companies should challenge actuaries to bring the best parts of innovation and risk management—explicitly make space for both. As insurance companies build new analytics capabilities, actuaries can be the best translators between the data scientists and the business. It’s the skill set that crosses quantitative skills with economic results and translates theory into practice. That description has been our message to candidates considering the profession. The world is full of complex and interconnected risks. The complexity is only increasing. In the long term, we believe the actuarial skill set will become more critical in helping society navigate this complexity. Actuarial science will also become essential in industries outside of insurance and healthcare. The profession has an exciting journey ahead.