Insurance companies have been analyzing data longer than almost any other industry, starting way back before the advent of computers. Actuaries are essentially data scientists who study the potential impact of risk, analyze data, and attempt to minimize the negative impact of unforeseen events as they occur. Although actuaries are best known for the risk assessment work done for insurance companies, they also work extensively with financial planners and strategists, multinational corporations, consultant agencies, and federal, state, and local governments. In the wake of the Big Data craze, actuaries are finding themselves in more demand than ever. An incomprehensibly huge amount of data is being mined, stored, and analyzed daily. And that data can serve to broaden the scope of actuaries’ responsibilities while honing their predictions and assessments to a higher degree of accuracy. With the rise of Big Data, artificial intelligence, and the growth of the Internet of Things (IoT) technology, aspiring actuaries might consider earning an advanced degree like an online masters in business analytics or an online masters in data analytics with an eye toward actuarial science as a career.
What Actuarial Science Entails
An effective, successful actuary will be a Renaissance man of sorts (or woman, since more than 40 percent of actuaries are female, according to the Bureau of Labor Statistics). A well-groomed actuary will exhibit a deep well of knowledge in a number of different disciplines, from mathematics to psychology, computer skills, and even history. “Actuarial science may well be the most multidisciplinary of professions because almost any field of inquiry you can think of has implications for an actuary’s work,” writes Casualty Actuarial Society member Rick Gorvett, FCAS, PhD, in his blog post, “5 Reasons To Be An Actuary As A Career,” on PropertyCasualty360.com. “Modeling and evaluating potential catastrophic events requires knowledge of several sciences,” Gorvett says, “Understanding psychology and sociology are necessary to model human behavior in a risky environment. Finance and economics are the contextual basis for estimating the potential financial impact of risk. And try modeling terrorism risk without an understanding of socioeconomic and political issues on a global scale.” The perfect candidate for a career in actuarial science (according to the BLS) is someone who excels at mathematics, critical thinking, reading comprehension, and writing. An innate ability to speak persuasively, listen actively, and make quick decisions and sound judgments is also important. The daily workload of a professional actuary could include catastrophe modeling for a large corporation, pricing new products, reviewing financial data, managing insurance rates by location, writing reports for acquisitions, or collaborating on data discrepancies with analytic coworkers. “The typical day of an actuary is anything but typical. Actuaries, especially consulting actuaries, work in an environment of constantly shifting priorities,” claims Be An Actuary in the “Smart Work: Problem Solving, Critical Thinking, And More” section of its website. “The field is dynamic because it is influenced by outside forces such as current economic conditions (whether recession or growth), energy costs, legislation, judicial decisions, and technological innovations. No two days are ever the same.”
Actuarial Science In The Modern Age
Actuarial science will not escape the tidal wave of Big Data that is currently sweeping over the land. But in this case, change will mean more accurate predictions based on real-time data, better and faster analysis of risk, much more personalized service, and the automation of the more mundane side of actuary work. Big Data will free up actuarial professionals to tackle problems that are more complex, and to expand their skillset, if necessary. The field of business analytics is bound to walk hand in hand with actuarial science, so a thorough knowledge of analytics and associated technologies will soon be essential learning for actuaries. The IoT will also have a major impact on actuarial science, especially in the insurance industry. Connected sensors of all sorts are now in place in products, vehicles, medical equipment, commercial facilities, and private residences. These IoT sensors are generating valuable data that can be used to pre-emptively correct defects or weaknesses before they become huge expensive problems. Big Data is already providing valuable insight into healthcare by organizing unstructured data regarding individual patients from multiple sources. Retail organizations are experiencing vast improvements in personalized marketing, efficient distribution, and predicted surges in demand. Crime prediction and prevention insights are now possible with a much higher degree of accuracy in the realm of politics. And instances of insurance fraud are much easier to discover thanks to Big Data. “Car insurance premiums are calculated based on dynamic causal data, including actual usage and driving behavior,” states the Institute of Actuaries in Belgium in its “Big Data: An Actuarial Perspective” information paper from 2015. “Telematics data transmitted from a vehicle combined with Big Data analytics enables insurers to distinguish cautious drivers from aggressive drivers and match insurance rates with the actual risk incurred.” Actuaries working in any industry need to be aware of Big Data and how it is affecting actuarial science now and will continue to do so in the near future. Since actuaries were doing analytics the old-fashioned way long before Big Data was born, they are already positioned to seamlessly adopt data analytics and make the most of the insights it provides.
Maryville University’s Master Degree In Business Data Analytics
The demand for business analytics experts lies at the heart of Maryville University’s online Master’s of Science in Business Data Analytics degree. Graduates of this online degree program will be fully prepared to enter the workforce as an actuary, data analyst, data scientist, or a statistician. At Maryville University, students learn how to handle datasets, orchestrate multiple infrastructures, monetize data, and make decisions based on valuable analytics insights. Graduates will have the training and knowledge to combine business operational data with the latest analytical tools, making them invaluable to employers.