I’ve always loved reading and learning about data mining and its applications in various fields. Because of this,Â Charles Duhigg’s comprehensive look at the consumer profiling practices of credit card companies was my favourite read over the weekend.
[Researchers] emphasized that the biggest profits didn’t come from people who always paid off their bills but rather from less-responsible clients who never paid their entire balance. [â€¦]
But giving credit cards to riskier customers posed a problem: How do you know which cardholders will pay something each month, providing fat profits, and which will simply run up a huge tab and then disappear?
[One] solution was learning to predict how different types of customers would behave. Card companies began running tens of thousands of experiments each year, testing the emotions elicited by various card colors and the appeal of different envelope sizes, for instance, or whether new immigrants were more responsible than cardholders born in this country. By understanding customers’ psyches, the companies hoped, they could tell who was a bad risk and either deny their application or, for those who were already cardholders, start shrinking their available credit and increasing minimum payments to squeeze out as much cash as possible before they defaulted.
There are some fascinating insights in the article, and throughout I was reminded of this Marissa Mayer quote (from her Charlie Rose appearance), taken from Super Crunchersâ€”a book on number analysis and data mining:
Credit-card companies can tell whether a couple is going to get divorced two years beforehand, with 98% likelihood.
The validity of that statement seems slightly dubious, but I love it nonetheless.