Predictive Analytics: Predicting the Future Through Numbers

Actuarial Director, CNA Insurance

Nov   2013



Seven out of every 10 actuaries work for an insurance company. That may sound like a pretty boring statistic, but being an actuary is way more interesting than you might think.  

As an actuary, I help clients predict and assess risky events that the everyday customer may never imagine. How risky? Here are a couple of examples.

While they may not realize it now, decision makers for a local hospital might need to start worrying about how an oncoming storm could knock out power and destroy millions of dollars in vaccines that their backup generator will fail to protect.

Or perhaps the chief security officer at the bank where you keep your life savings is sleeping soundly now, but will soon be kept up at night by visions of cyber hackers stealing the access information of the bank’s customers.

Predicting the future

As an actuary, I don’t just imagine nightmare scenarios like this; I predict how they might play out, how often they will happen, and at what cost. This ability to accurately forecast and measure risk before losses occur helps my employer ensure revenue growth and competitive advantage for our clients, while keeping rates fairly priced.

This begs the question, how does one learn to predict the future? Is there a master’s degree for students and professionals seeking to hone their ESP skills? Not quite. But if you’re a student or a professional seeking to deliver this unique form of value to business customers, I can tell you about a high-demand skill set that is being taught around the world and will allow you to differentiate yourself—big time—in the job market.

It’s called “predictive analytics.”

New careers for numbers people

In terms of abilities, I’d define myself as a classic numbers person. In high school, I excelled at math and exhausted the math courses offered through advanced calculus and statistics. In college, I majored in math and economics. And in the working world, I obtained my professional designation in actuarial science, a field that applies statistical methods to assess risk for insurance and financial services companies.

But make no mistake: math alone cannot position you as a top candidate for jobs in actuarial science, or any area of risk management for that matter. Insurers and their clients are faced with a deluge of big data relating to risk characteristics, claim activity, and financial transactions, as well as sales and marketing statistics. And these organizations are urgently seeking professionals who are skilled in the art of uncovering valuable insights from data and, in turn, transforming those insights into risk-minded strategies.

This is creating new careers and professional opportunities across industries. And in the insurance world, it’s all about the ability to model future risks by determining the relevant data and incorporating business insights to create meaningful analysis.

How to stand out in the crowd

So how can one land a career in this fast-emerging field?

Well, in a marketplace that is saturated with numbers people like me (there are over 20,000 actuaries across the United States, based on public data), you really have to differentiate yourself, if you want to be the data-crunching guru today’s businesses need. And for me, this meant adding two important skill sets to my math background: predictive analytics and business strategy.

Where can you find training like this? The recent explosion of data has inspired higher education programs around the world to develop a new focus on big data and analytics courses, curricula, and complete majors. In my particular case, I enrolled in a new program at Northwestern University’s School of Continuing Studies, recently launched in conjunction with IBM, which has partnerships with more than 1,000 universities across the globe focusing on big data and analytics skills.

Through that program, I gained deeper insights into how predictive models are built and how they can be used in a business setting. That, along with my knowledge of how the insurance business works, enables me to more effectively communicate and earn buy-in for new and valuable initiatives at my company.

Bringing data to life

Communication and buy-in are crucial if you want to implement new data-driven recommendations in any business setting. As you might suspect, simply putting a handful of complicated graphs and formulas in front of an audience with limited statistics knowledge would result in a lot of confusion and frustration. However, translating the complex math into a story of why certain risks are less profitable or why we should grow in a certain area is a more engaging conversation.  

This is a data-driven world, no matter what field you choose to pursue. And having the ability to understand data—to truly draw valuable insights from data and communicate those findings—will set you ahead of the pack in the job market where there is great demand for big data and analytics professionals.  

And if you take a moment to look online at universities’ business, engineering, and computer science programs, chances are you’ll find they now offer at least one class—if not an entire undergraduate or graduate program—to help prepare you for the field of big data and analytics.

If you’ve read this and you’re now thinking about upping your big data game . . . well, I can’t predict the future, but all the data I have analyzed suggests this new way of thinking will lead to good things!

Note: The views expressed by the author are her own and may not necessarily reflect those of her employer.

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About Kimberly Lacker

Kimberly Lacker is the Actuarial Director, CNA Insurance. She received a Master of Science in Predictive Analytics from Northwestern University in 2013.