Recently I've written about the large numbers of American consumers — as many as 30 to 35 million — who are "credit invisible." Almost 10 million of them could be creditworthy but they are essentially shut out of the mortgage market because they lack the conventional credit scores most lenders use to determine whether someone qualifies for a mortgage. I've also discussed the impact this has on the housing economy, as well as the specific effects on consumers and lenders. But what can be done about it?
The first step toward correcting this problem for millions of potential borrowers is to change the way we think about credit scores. We need to understand that conventional credit scores have limitations, and as such, they do not provide a complete picture of how every borrower handles money.
In fact, the conventional scoring models used by most mortgage lenders, as required under Fannie Mae and Freddie Mac's seller/servicer guidelines, have not been updated since before the housing crisis (and some models still in use have not been updated in over a decade). These scoring-model mandates force lenders to use outdated, pre-recession models developed using data spanning 1995 to 2000.
I ask you: Have consumer credit behaviors have changed since the '90s? Of course they have. Have new, highly predictive data been introduced since the '90s to help score more people? Of course they have.
A step toward solving the "credit invisibles" problem is to let lenders seek out and utilize newer, more innovative methods of measuring a borrower's risk of default. To allow that, these housing agencies and the secondary market must make room for these more advanced tools in the risk-assessment guidelines they provide to lenders.
In other words, we need to change the way we think, and then change the way we act — and that is hard.
But there is good news. Advanced scoring models are not only readily available from a number of model developers, they are already in use across all sectors of the consumer credit industry.
In fact, many top lenders, credit unions and even mortgage companies already rely on newer credit scoring models when originating loans and monitoring portfolios. So do many secondary market participants, who use them for evaluating default risk and in order to price loan pools with greater precision.
These models are also embedded into most major industry platforms and data standards, including Mortgage Industry Standards Maintenance Organization standards, the Consumer Financial Protection Bureau-Federal Housing Administration mortgage database, and the Federal Housing Finance Agency's Common Securitization Platform. They are used in reporting forms accepted by the Structured Finance Industry Group on available-for-sale and asset-backed securities issues; and in major software that communicates with the credit reporting companies' credit files. They are also used in the private-labeled mortgage-backed securities market to enable more detailed and predictive measurement of default risk in previously issued securities.
For all the acceptance newer scoring models have received, the vast majority of the mortgage industry remains stuck in the same behavior patterns, unwittingly holding back millions of would-be homeowners from achieving the American dream. Meanwhile, conventional scoring models are growing increasingly outdated, disenfranchising large numbers of Americans.
For this reason, more and more industry groups are calling for greater choice among credit scoring models. Organizations speaking out on this issue include the American Financial Services Association, the Consumer Federation of America, the National Consumer Reporting Association, the National Association of Hispanic Real Estate Professionals, the National Community Reinvestment Coalition, the Asian Real Estate Association of America and the Woodstock Institute.
Thankfully our collective voices have been heard. Last month in American Banker, both Fannie Mae and Freddie Mac disclosed they are embarking upon an analysis regarding the adoption of new credit scoring models. Assuming their analysis demonstrates significant benefits and reasonable costs, new methods of measuring consumer credit risk will enable mainstream lenders to score consumers more effectively and inclusively.
A more accurate picture of risk carries benefits to the MBS markets, too. And for the consumer — especially the underserved, "invisible consumer, banished from view only because he or she doesn't have a conventional credit score — there is greater access to credit.
If you ask me, bringing those credit invisibles who are actually credit worthy is the right thing to do on so many levels. What do you think?