A recently released government study by the Consumer Financial Protection Bureau on “Credit Invisibles” has some interesting facts on people with and without credit histories.
Percentage Share of Invisibles and Unscored by Age
Number of Invisibles and Unscored by Age
Credit Expansion
The study did not indicate how many of the 45 million (invisibles plus unscorables) are illegal aliens. But the name of the game as always is credit expansion.
Investor’s Business Daily discusses situation in Obama Pushing Banks Into Riskiest Borrower Pool Yet: 45 Million ‘Unscorables’.
Housing: As part of its amnesty program, the Obama regime seeks to expand credit to a whopping 45 million potential deadbeats — including illegal immigrants — whose credit files are too spotty even to score for risk.
In a just-released federal report, the administration portrays these “credit invisibles” as victims of a traditional credit-scoring system. And since most are minorities, it claims that excluding them from the financial mainstream is discriminatory.
“Our report found that black and Hispanic consumers are more likely than white or Asian consumers to have limited credit records,” CFPB Director Richard Cordray said in a press call.
To remedy the “credit inequality,” credit reporting agencies are being pressed to generate scores for this high-risk group based on payments of cellphone and utility bills, as well as immigrant remittances.
But analysts say most of these “unscorables” are not creditworthy, and according to preliminary estimates, their median credit score falls well below the subprime cutoff (535 vs. 620). Public records show many are subject to third-party debt collection and tax liens.
Lenders rely on the three-digit credit score as an indicator of how likely it is a borrower will repay a debt. Stale files or thin credit history does not allow FICO and other risk modelers to accurately predict future credit performance — that is, the likelihood, relative to other borrowers, that a consumer will become 90 or more days past due on a credit obligation in the following two years.
Using “alternative” inputs in the models, such as utility payments and remittances, could water down the models and make credit scores less reliable, leading banks to make even riskier lending decisions.