Adapting Actuaries

Within the past decade, I have witnessed rapid changes in the requirements and functions of actuaries. This transformation has been driven by the need for improved processes and cost efficiency, as well as the changing needs of insurance consumers. The analytical aspect of an actuarial role has become more complex, and the skill sets and challenges have changed substantially. As a result, the training and education for becoming an actuary were updated.

Technological Transformation

Without a doubt, the role of an actuary is centered around technology. Most actuarial work involves modeling, ranging from dealing with data for assumption-setting, to creating pricing and valuation models, to building pro-forma financial statements. Often, the end-to-end process is complex and involves substantial manual work, particularly in pre- and post-model run infrastructures.

Over time, actuaries have recognized the importance of automation in repetitive and time-sensitive processes. Being able to turn around analyses quickly allows more time for strategic planning and testing alternative solutions for further insights. The desires for cost efficiency and to stay competitive also have facilitated process optimization at many companies. Today, being able to code automation programs in Excel VBA is essential for most actuaries.

Alongside the move toward automation is incorporating different platforms to complement Microsoft Excel, which has long been the most common application in an actuarial role. For example, when dealing with a large volume of data for analysis, programs such as SQL, R, Matlab or Python can be more efficient when compared to Excel. Being able to adapt the right technology better positions actuaries to handle challenging situations efficiently.

Regulatory updates are accelerating the need for further process streamlining. Recently, International Financial Reporting Standard (IFRS) 17 and U.S. Generally Accepted Accounting Principles (GAAP) Long-Duration Targeted Improvements (LDTI) are forcing insurance companies to consider wider system transformations. Existing valuation systems may need to be updated or switched to meet new requirements. New processes and controls need to be in place for the complex reporting requirements as well. Integrating automation and new technologies will be important elements to give actuaries and other professions enough time to review outcomes from this major reporting update.

Clearly, the technology required for actuaries to do their jobs is increasing and changing rapidly. As the actuarial profession moves toward a more automated and advanced future, certain roles and skills may become obsolete, which will create more competition among the actuarial talent pool.

Influences from InsurTech and Big Data

Today’s economy is an internet-based one in which information and services can be accessed on the go. As the economy continues to evolve, we have witnessed several major disruptions in traditional businesses across many industries. For example:

• Uber challenged the taxi business.
• Apple revolutionized the mobile market.
• Amazon even targeted grocery stores by purchasing Whole Foods.

The insurance industry is no exception when it comes to this power of change driven by technology. InsurTech innovations embrace this change in consumer mindset and aim to develop products and services that are more attractive to millennials and an increasingly tech-savvy population. The disruption and competition from InsurTech create new and exciting opportunities for actuaries. In addition to working at established insurance companies, actuaries now have exposure to different industries where the focus is on innovation and leveraging technology.

The most notable movement stemming from the InsurTech trend is the big data wave. In the past, there was significant information asymmetry. Insurers often didn’t know much about a customer’s health or behavior over the life of a policy, and as a result, they lacked information about the evolution of risk factors in pricing products. To solve this issue, the entire industry is moving toward building optimized product designs using insights from big data. In the case of life insurance, consumers are incentivized to share lifestyle and health-related behaviors with insurers, and in return, they receive discounts on insurance products (if they maintain their healthy habits). In this model, insurers gain by receiving more data to better select risks and generate higher retention and loyalty, while consumers benefit from discounts and personalized programs for improving their own health.

In the long term, data analytics will help insurers analyze specific consumer situations, give advice and develop product solutions that are tailored to consumer needs. Many insurance companies are adding advanced analytics functions for enhancing product development. Reinsurance companies are doing the same and working closely with direct insurers on gaining insights from data while providing reinsurance protection on new product designs at the same time. Actuarial consulting firms are also in the game, adding resources for predictive analytics solutions. These new functions create opportunities for actuaries who already are equipped with statistical knowledge from core insurance functions. Actuaries will need to tap into more advanced artificial intelligence (AI) and machine learning techniques compared to the methodologies used in traditional actuarial roles.

Actuarial Credential Pathway Changes

Professional organizations that provide actuarial training and education are constantly updating their curricula to ensure actuaries are equipped with the essential skills to meet employer and market demands. Future actuaries need to master these new knowledge areas to earn the actuarial credential.

For example, the Society of Actuaries (SOA) recently introduced exams related to predictive analytics to prepare actuaries for opportunities in the newly created advanced analytics function. R programming is incorporated in these exams for data analysis, providing exposure to a data-oriented computing platform that is a good complement to the traditional Excel. R programming is introduced in several online learning modules to prepare actuaries for processing large amounts of data efficiently. Besides the data application, exposure to R programming also gives actuaries the algorithmic mindset that’s often needed when utilizing applications such as SQL or Python for implementing efficiency and productivity improvements in day-to-day tasks.

In addition to the inclusion of data-related elements in credential pathways, the introduction of Chartered Enterprise Risk Analyst (CERA) in 2019 provides actuarial professionals a path to a broad range of enterprise risk management roles. Traditional actuaries are subject-matter experts on dealing with future uncertainties and managing risks, and their quantitative and qualitative perspectives on risk are applicable beyond the insurance industry. The CERA curriculum leverages foundational actuarial training, and its education pathway overlaps with requirements for becoming a credentialed actuary. This new designation provides actuaries with interesting job opportunities in risk functions, such as investment management, banking or other financial services.

Besides education for upcoming actuaries, professional development for current actuaries also focuses on the emerging market needs to ensure the profession stays on top of recent trends.

The Future of the Actuarial Profession

Changes to the actuarial profession do not end here. For instance, there may be long-term implications from the COVID-19 pandemic that will change consumer behavior and the landscape for digitization again, which will impact how actuaries look at insurance-related insights. Overall, the key to success in the actuarial profession is adapting and embracing change as an opportunity for professional development and improvement.

Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries or the respective authors’ employers.

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