Is it possible that an analysis of your collective data profile could label you as a poor risk or a desirable candidate for a life insurance policy? Not only possible, but happening now, according to an article published November 19, 2010 in the Wall Street Journal. Deloitte Consulting LLP is marketing a process called predictive modeling to major life insurance providers. It allows them to predict your life expectancy based on your behavior, which in turn lets them decide whether or not you’d be a profitable policy customer. If this comes as a shock to you, you haven’t been paying attention.
Direct marketers have been slicing and dicing your behavioral data for decades and using it to determine your likelihood to buy everything from encyclopedias to collectible sock monkeys to thimbles of the month. With the advent of the Internet it just all got easier because of the proliferation of data points, most of them supplied by you when you shop online. Sophisticated marketers use a cumulative analysis of your behavior to target you for pitches you’re likely to be interested in. Conversely, they don’t waste marketing dollars and resources trying to sell you something your past behavior says you’ll never buy. It doesn’t mean you wouldn’t be open to purchasing a life-size porcelain Elvis, they’re just not going to spend any time or money finding out.
Life insurance companies are very sophisticated marketers and are testing predictive modeling to see if what you do, read, eat, buy or otherwise consume puts you at risk of disease and early death. For example, if they see that you buy a magazine called Growing and Curing Your Own Tobacco, routinely purchase cigarettes using your supermarket club card and use your credit card to pay for several evenings a month at your local hookah smokers club, they can reasonably assume you’re A(a tobacco user and B)statistically at risk of developing emphysema or cancer at a higher proportion than the rest of the population. If, on the other hand, they see that you belong to a health club, subscribe to Jogging for Health & Fitness, buy six pairs of running shoes a year and shop for groceries at the local Totally Healthy Foods Mart, they can logically conclude that A) you live a healthy lifestyle and B) are more likely to live to a ripe old age. Which profile do you think makes you the ideal candidate for a life insurance policy?
Life insurance companies that are testing the predictive modeling say it could actually lower life insurance premiums because it costs the providers less to screen candidates. Currently, insurers use costly blood and urine analyses to assess an applicant’s health. They claim the predictive modeling process can tell them almost as much as those expensive tests. Anything that lowers the cost of underwriting a life insurance policy is good for the consumer.
According to the article in the WSJ, Deloitte Consulting LLP and its life insurance company clients said the database info they gather would never be used to “make final decisions about applicants.” It would simply expedite the application process for low-risk applicants. All others would go through the traditional testing.