The US Department of Homeland Security has published a new proposed rule that would make people ineligible for US citizenship if their credit-scores were poor.
Notionally, the rule-change is meant to prevent immigrants from becoming burdens on the welfare system (migrants do not make disproportionate use of any public welfare system).
However, the credit reporting bureaus are notoriously inaccurate and arbitrary in the credit-scores they assign; if you have a lot of assets but do not borrow money, you will have a much lower credit-rating than if you unwisely enroll in a number of high cost/high fee store cards and pay them off after running up debts on them and paying significant interest (I am allergic to debt, and with the exception of my mortgage have no debts at all; because of this I have a fairly low credit-score, despite the fact that both my wife and I earn very good livings).
What’s more, the credit-reporting sector is riddled with security holes; notoriously, Equifax doxxed the entire adult population of America by breaching more than 150 million residents’ financial data. Integrating credit scores into the immigration process will grant the bureaux a permanent government contract and funnel tax-dollars to them forever, despite their routine errors, racial bias, and spurious guilt-by-statistical-association.
Finally, the DHS’s change is an appeal to selfishness and cruelty: if America is unwilling to accept migrants who are indigent or who need assistance, what does it say about us as a nation?
It’s a Made-in-America version of China’s notorious Citizen Scores.
Makes sense, right? People with low credit scores are loafers and can’t be trusted to take care of themselves. Unfortunately, this is not what traditional credit scores measure. They are specialized algorithms designed for one purpose: to predict future bill-paying delinquencies, for any reason. This includes late payments or defaults caused by insurmountable medical debts, job loss, and divorce—three leading causes of personal bankruptcy—as well as overspending and poor money management.
Credit scores do not distinguish between these various causes. A person whose score plunges because of sudden unemployment is the same as a person sunk by foolish spending sprees. Credit scores can also be wrong if the underlying data in credit files is flawed. A Federal Trade Commission study found “potentially material errors” in 1 in 5 credit reports.
DHS’s proposed use of credit scores points to a much larger problem involving metrics. As more of our everyday interactions produce data, more of our lives can be quantified and turned into scalable measures. Our productivity, health and fitness, internet searches, and consumer behavior are all converted into behind-the-scenes metrics. Our social connections—numbers of friends, followers, likes, and retweets—are displayed as public tallies. We even score each other, Black Mirror–style, on ride-sharing apps.