Actuaries and Actuarial Science
But even the simple problems are deceptive. Let's revisit the risk of stepping out in front of a moving car. Certainly, there's a risk that the wayward pedestrian gets hit. But what if the driver swerves? Are there cars in the other lane? If so, what kind of cars? The difference between swerving into the path of a Toyota Camry and an 18-wheeler is profound. And what about the cars behind the car in front of which the pedestrian stepped out? What if the person hit by the car is thrown into the other lane? Or the sidewalk? As you can see, one simple (and admittedly macabre) action has a million possible outcomes, and a million possible risks involved. Of course, in this case, having the pedestrian not walk into the street mitigates all of those risk factors.
The above example consists of one variable -- whether the pedestrian takes the wrong step off a curb. Now ponder how an actuary might manage risk within a life insurance company with two million policyholders. The life expectancy of one person takes into account hundreds of variables, including eating habits, smoking, drinking, where the person lives, what he or she does for a living, family life, number of children, pets, family history of illness & the list goes on. Then multiply that by two million, and finally ask yourself the big question: How much should each person pay each month so that the company can fulfill its payout obligations to each and every one of them at the end of their lives, whenever that might be?
Answering that question is at the very core of what actuaries do. Through advanced probability models and statistical analysis, actuaries make the assumptions needed to ensure that insurance policies, pensions and other financial programs meet their obligations and, ideally, make a profit for the companies running them.