If you pay your bills on time, then you're probably also a good driver. This statement might come as a surprise to you, and Fair Isaac Corporation CEO Mark N. Greene says his firm didn't expect this result either. But over the years, auto insurers noticed a correlation between his company's FICO credit scores and their customers' driving records. As any good business would, FICO saw this as an opportunity. It has begun to expand its offering of analytical products to appeal to businesses other than just lenders.

Greene explains that his company is expanding its effort in "behavioral analytics." So far, it has identified four sectors that can benefit from studying consumer behavior: auto insurance, health care, banking, and retail. By tracking data on how people have acted in the past, FICO can provide valuable predictive models to companies on how consumers will act in the future.

Health care is another industry that you might not expect FICO to be able to employ behavioral analysis. It turns out that many people with imperfect credit scores are also imperfect patients. Greene explains that his company has found that these individuals often don't take their medication as indicated and don't adhere to health care regiments set up by doctors. As a result, its expanded health care analytic, which considers other behavioral factors as well, can help medical professionals to know which patients might need more guidance, additional reminders, and extra encouragement to follow doctors' orders.

Perhaps the most fascinating predictive power that FICO has been working on serves retailers. Some companies, such as Sam's Club, hire FICO to try to better understand their customers. By analyzing things like the prices of items consumers purchase, when they shop, the items they buy together, how many things they purchase at a time, and other such behavioral metrics, they can hypothesize what, how, and when a customer will buy in the future. And these predictions can be very precise.

Retailers gather such information through means like loyalty programs. FICO then analyzes that data and provides predictive models to the companies. Retailers use these predictions to encourage consumers to make specific purchases in the future through encouragement like targeted coupons. According to Greene, redemption of those coupons sometimes approaches rates of 30%, while such coupons offers only traditionally had redemption rates of 1% to 2%.

Banks found a way to utilize enhanced analytical tools as well. They recently got hit with significant new regulations on credit and debit cards. Those new rules will put a big dent in profits. Some experts have suggested that these financial institutions will be forced to increase fees elsewhere, like charging maintenance fees for services like checking, which has long been free for many consumers. But Greene says that FICO's analysis also shows that banks might find ways to increase their profits in ways other than charging for checking. By understanding consumer behavior better, banks can instead make up some of that lost revenue by knowing which of its other products might interest specific customers and marketing accordingly.

One area where FICO isn't expanding its scoring methodology is to help prospective employers learn more about how job applicants might perform. Last year, the practice of companies performing credit checks on prospective hires got some attention in the press. Greene said FICO scores could possibly help selecting applicants for a job with money-related duties, where financial management was applicable. But he does not believe that credit worthiness is a good way to judge potential employees, in general.

There are a few ways you can view such expanded behavioral analyses. Of course, some people will interpret them as another way in which corporate America is trying to get inside their heads. Retailers, for example, want to know what you intend to buy possibly even before you do.

But such analyses could also be good for consumers. Deals and bargains tailored to each individual customer are better than arbitrary offers that might only appeal to a handful of people. For example, if a predictive model correctly guessed that you were planning on buying a Blu-ray player, because you recently purchased a big screen TV, then a coupon offered by a retailer might save you some money on a purchase you would have made anyway.

Whether it's good or bad, behavioral analytics are likely going to play a big role going forward. As more data on consumer activity is collected by various firms and sectors, companies like FICO will have ample opportunity to offer a very valuable service to firms.