Alternative Credit Reporting
In the last 25 years, credit has taken on an increasingly important role in our economy. Yet, an estimated 50 to 70 million Americans remain un-scored or have a thin credit file, meaning that the big three U.S. credit bureaus (TransUnion, Experian and Equifax) do not have enough information about these individuals' finances to assign them a credit score, whether good or bad. Accumulating assets is necessary for low-income families to move out of asset poverty and become financially secure.
Without a credit history, it is difficult, if not impossible, to qualify for a mortgage, obtain a credit card, buy a car, or finance a small business. Increasingly, even employment and rental housing decisions hinge on a credit score. These computer-generated scores have, in just a couple of decades, become the benchmark for lending. Banks use credit scores to determine eligibility and pricing for loans. Although banks argue that standardization of credit scoring has enabled millions of consumers to get loans quickly and at a low price, without regard to race, gender, or residence, estimates indicate that 32 million consumers have credit files that are too thin to score, and 22 million have no files at all. Many of the “un” or “under” scored are minorities, young adults, and women.
Most credit scores are based on some variation of Fair Isaac's FICO score, which ranges from 300 to 850. The lower the score, the greater the risk. The main factors used in a FICO score are payment history for credit cards, mortgages, and other retail accounts, the amount a consumer owes, the length of time he or she has held credit, and the amount of recently opened credit cards. In order to increase access to credit, some advocates are calling for the inclusion of alternative data in credit reporting.
A 2006 study indicated that an overwhelming majority of lenders believe that increasing numbers of individuals could borrow money if nontraditional data were incorporated into lending decisions. In fact, half of the lenders interviewed in this study said that they were already using or evaluating the use of alternative data sources. Yet, a closer look at the credit reporting system seems appropriate before incorporating such data.
If, as some claim, the current credit system’s lack of transparency and inaccuracy already discriminates against low-income families, should we first work on making the credit bureaus accountable and transparent before adding more information into a seemingly vacuous and obscure system? If a new reporting system is needed, how should it be constructed so that minorities and low-income workers do not become even more vulnerable?
Moreover, not all alternate credit reporting and scoring methodologies are created equal. What types of data predict creditworthiness and should therefore be reported? Should it be limited to data such as rent, telecom, and utility payments? Should alternative data reporting also include things such as child care, medical, and other payments not currently or routinely examined by the large credit-reporting agencies? As part of incorporating such alternative data, should the reporting process be adjusted to provide an opt-in for those who want it, rather than automatic reporting for all? Or should extra weight be given to payments, such as child support, thereby making credit scoring not only a predictor of creditworthiness, but also a basis for social policy?
The Shriver Center is hosting a webinar to explore the effect alternative data reporting will have on low-income families. Join us on May 27th at 1 p.m. CDT to learn about current research on the impact of alternative data reporting based on firms that already report both on-time and late payment, including full data reporting of NICOR and DTE customers; current gas and electric utility credit and collection data from states around the country; the National Credit Reporting Association’s perspective on alternative credit reporting, and proposed legislative amendments to the Fair Credit Reporting Act.
This article was coauthored by Susan Ritacca.
