Let’s compare that to the 1950s-era banker. Consciously or not, that banker was weighing various data points that had little or nothing to do with his would-be borrower’s ability to shoulder a mortgage. He looked across his desk and saw his customer’s race and drew conclusions from that. The customer’s father’s criminal record may have counted against him or her, while regular church attendance may have helped.
All of these data points were proxies. In his search for financial responsibility, the banker could have dispassionately studied the numbers (as some exemplary bankers no doubt did). But instead, he drew correlations to race, religion and family connections. In doing so, he avoided scrutinizing the borrower as an individual and instead lumped him in a group of people — what statisticians today call a bucket. “People like you,” he decided, could or couldn’t be trusted.
Fair and Isaac’s great advance was to ditch the proxies in favor of the relevant financial data, like past bill-paying behavior. They focused their analysis on the individual — not on other people with similar attributes. E-scores, by contrast, march us back in time. They analyze the individual through a veritable blizzard of proxies. In a few milliseconds, they carry out thousands of “people like you” calculations. And if enough of these “similar” people turn out to be deadbeats or, worse, criminals, that individual will be treated accordingly.
The Problem With Proxies
From time to time, people ask me how to teach ethics to a class of data scientists. I usually begin with a discussion of how to build an e-score model and ask them whether it makes sense to use “race” as an input in the model. They inevitably respond that such a question would be unfair and probably illegal. The next question is whether to use “ZIP code.” This seems fair enough, at first. But it doesn’t take long for the students to see they’re codifying past injustices into their model. When they include an attribute such as “ZIP code,” they’re expressing the opinion that the history of human behavior in that patch of real estate should determine, at least in part, what kind of loan a person who lives there should get.
In other words, the modelers for e-scores have to make do with trying to answer the question “How have people like you behaved in the past?” when ideally they would ask, “How have you behaved in the past?”
I should note that in the statistical universe proxies inhabit, they often work. Birds of a feather do tend to flock together. Rich people buy cruises and BMWs. All too often, poor people need a payday loan. And since these statistical models appear to work most of the time, efficiency rises and profits surge. Investors double down on scientific systems that can place thousands of people into what appear to be the correct buckets. It’s the triumph of Big Data.
But what about the person who is misunderstood and placed in the wrong bucket? That happens. And there’s no feedback to set the system straight. A statistics-crunching engine has no way to learn it dispatched a valuable potential customer to call center hell. Worse, losers in the unregulated e-score universe have little recourse to complain, much less correct the system’s error. In the realm of WMDs, they’re collateral damage. And since the whole murky system grinds away in distant server farms, they rarely find out about it. Most of them probably conclude, with reason, that life is simply unfair.
Credit Is a Virtue
In the world I’ve described so far, e-scores nourished by millions of proxies exist in the shadows, while our credit reports, packed with pertinent and relevant data, operate under rule of law. But sadly, it’s not quite that simple. All too often, credit reports serve as proxies, too.
It shouldn’t be surprising that many institutions in our society, from big companies to the government, are on the hunt for trustworthy and reliable people. So when it comes to hiring, an all-too-common approach is to consider the applicant’s credit score. If people pay their bills on time and avoid debt, employers ask, doesn’t that signal trustworthiness and dependability? It’s not exactly the same, they know. But wouldn’t there be a significant overlap?
That’s how credit reports have expanded far beyond their original turf. Creditworthiness has become an all-too-easy stand-in for other virtues. Conversely, bad credit has grown to signal a host of sins and shortcomings that have nothing to do with paying bills.
For certain applications, such a proxy might appear harmless. Some online dating services, for example, match people based on credit scores. One of them, CreditScoreDating, proclaims that “good credit scores are sexy.” We can debate the wisdom of linking financial behavior to love. But at least the customers of CreditScoreDating know what they’re getting into and why. It’s up to them.
But if you’re looking for a job, there’s an excellent chance that a missed credit card payment or late fees on student loans could be working against you. According to a survey by the Society for Human Resource Management, nearly half of America’s employers screen potential hires by looking at their credit reports. Some of them check the credit status of current employees as well, especially when they’re up for a promotion.
Before companies carry out these checks, they must first ask for permission. But that’s usually little more than a formality; at many companies, those refusing to surrender their credit data won’t even be considered for jobs. And if their credit record is poor, there’s a good chance they’ll be passed over. A 2012 survey on credit card debt in low- and middle-income families made this point all too clear. One in 10 participants reported hearing from employers that blemished credit histories had sunk their chances, and it’s anybody’s guess how many were disqualified by their credit reports but left in the dark. While the law stipulates employers must alert job seekers when credit issues disqualify them, it’s hardly a stretch to believe some of them simply tell candidates they weren’t a good fit or that others were more qualified.
The practice of using credit scores in hirings and promotions creates a dangerous poverty cycle. After all, if you can’t get a job because of your credit record, that record will likely get worse, making it even harder to land work. It’s not unlike the problem young people face when they look for their first job — and are disqualified for lack of experience. Or the plight of the longtime unemployed, who find that few will hire them because they’ve been without a job for too long. It’s a spiraling and defeating feedback loop for the unlucky people caught in it.
Employers, naturally, have little sympathy for this argument.
Good credit, they argue, is an attribute of a responsible person, the kind they want to hire. But framing debt as a moral issue is a mistake. Plenty of hardworking and trustworthy people lose jobs every day as companies fail, cut costs, or move jobs offshore. These numbers climb during recessions. And many of the newly unemployed find themselves without health insurance. All it takes is an accident or an illness for them to miss a loan payment. Even with the Affordable Care Act, which reduced the ranks of the uninsured, medical expenses remain the single biggest cause of bankruptcies in America.
This isn’t to say personnel departments across America are intentionally building a poverty trap. They no doubt believe credit reports hold relevant facts that help them make important decisions. After all, “the more data, the better” is the guiding principle of the Information Age. Yet in the name of fairness, some of this data should remain uncrunched.