The digital age presents myriad new opportunities for actuaries, especially in data science, machine learning, artificial intelligence, risk management and predictive models. In this interview, Alejandro Sokol and Rodrigo Meyer, partners of actuarial solutions at Lisicki, Litvin & Abelovich, explain how the actuarial profession is evolving beyond traditional insurance and pensions into areas that are increasingly relevant for businesses today. They also illustrate how actuaries are well positioned to solve data-driven problems, assess risk, improve decision-making and create value in a rapidly changing market.
Federico Tassara (FT): To begin, why are we talking about new horizons for the actuary’s work?
Alejandro Sokol (AS): If we were to analyze the actuary’s areas of responsibility over time, we would clearly find different stages. Initially, the actuary’s work was oriented to the world of insurance, mainly with regard to the determination of life insurance premiums and mathematical reserves. The next, almost obligatory, stage occurred with the upsurge of national pension and social security systems. Although this originated at the end of the 19th century, it only began to consolidate in the middle of the 20th century through participation in the development of sustainability models.
Between 1970 and the new millennium, the actuary gained prominence in the world of modern finance, particularly with financial derivatives and everything related to the implementation of risk management tools and valuation models of financial instruments in conditions of uncertainty. There was a notable boost from certain milestones, such as the regulatory framework (Basel, International Financial Reporting Standards, central banks, and so on). The risk-based approach to business is becoming stronger, not only looking for profitability per se, but also adjusting to the level of risk assumed.
FT: How does one adjust the return to the risk assumed?
AS: Conceptually it is simple. Financial institutions, particularly banks, assume risks all the time (credit, liquidity, interest rates, prices). An annual return on fund placements, let’s say 4% in short-term US treasury bonds, is different than the same return on certain risky placements. Somehow it is necessary to “homogenize” the measurement. In other words, to make the “success” of placements comparable, one must compare not only the returns realized or expected, but also the risk assumed in each one. And actuaries, who are experts in risk assessment, are well prepared to do that kind of analysis.
FT: Returning to the fields of actuarial participation and new horizons, what’s next? What are the new trends?
Rodrigo Meyer (RM): Clearly, we work every day with issues related to data science and new technologies applied to the use of data. There has been a growing trend for several years now toward trying to understand customer behavior, and by this, I mean knowing expected future behavior. Needless to say, it is impossible to know how each person will behave in a particular situation, but if it is possible to estimate some specific behaviors with a certain degree of precision, decisions can be made that positively affect the business.
FT: Can you give us some examples?
RM: Of course. A very clear example is the implementation of customer retention models, which seek to identify early those customers who are about to abandon a product, package or service. Using retention models, the company may anticipate this fact and offer customers an improvement to retain them or design more effective loyalty programs. Another common example in the financial industry involves models for classifying customers based on their “credit quality,” or the probability that individuals/companies will repay the loans granted to them. It is also common in the financial industry and others to apply models to detect possible fraudulent or money laundering operations, so they can be reported or preventive actions taken. I could go on and on—product or service recommendation models; customer segmentation by behavior patterns and similar characteristics; prediction of delinquency models and intelligent collection for revenue management, which consist of maximizing income by trying to achieve the optimal sales conditions for each customer and moment.
FT: I understand a little of each of the examples you describe, but I don’t fully understand why you say that all these issues bring new opportunities for actuaries in particular. Can you explain this?
RM: All the examples I already mentioned, regardless of their complexity, have something in common: a strong load of mathematical and statistical foundations applied to a business problem. Actuaries usually solve practical problems using techniques and tools from the hard sciences, always with a management orientation. Our academic background coupled with industry experience makes us the ideal professionals to efficiently resolve issues related to data and uncertainty. In an environment where data is a key asset, this combination uniquely positions us to develop predictive models, assess risk and optimize business strategies. This not only allows us to generate valuable information, but also to translate it into concrete actions that improve the profitability and sustainability of organizations.
FT: Can you tell us about a specific case in your day-to-day experience with these issues?
AS: Among those that quickly come to mind is the example of clients who handle large volumes of data and have difficulty taking advantage of it in a timely manner. We help them develop learning models that not only use all available information to model customer behavior but also are automated and run quickly, enabling timely results for users to use in making decisions. High competition has also led many companies to become increasingly concerned about having more complex models to know their customers better, allowing them to offer better products or services, establish more effective loyalty programs and minimize the risk of adverse selection. In short, we develop solutions that allow us to generate useful information for decision-making from large volumes of data and machine learning or artificial intelligence models, which, as we said before, are basically statistical models.
FT: In your opinion, what are actuaries’ future prospects?
RM: I believe the outlook is extremely favorable. This is a process that began several years ago and is growing at an accelerated pace. All the issues that look innovative today will soon become commonplace. Therefore, I believe that actuaries must prepare for what is coming and continue learning. It is a great opportunity to expand the application of actuaries in the professional field, and it is within our grasp to take advantage of it. This growth also drives the development of other professionals, such as mathematicians, physicists or data scientists, who have gained great renown in recent times. For this reason, this opportunity also involves a risk: if we do not adapt to new market trends, we could actually lose ground against other professions that are on the rise.
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Federico Tassara, ASA, is business development manager Southern Europe & Latam at Munich Re. Federico can be reached at ftassara@munichre.com.
Alejandro Sokol, UBA, is a partner in actuarial solutions at Lisicki, Litvin & Abelovich. Alejandro can be reached at asokol@llyasoc.com.
Rodrigo Meyer, UBA, is a partner in actuarial solutions at Lisicki, Litvin & Abelovich. Roderigo can be reached at rmeyer@llyasoc.com.