Credit scores vary widely among racial, ethnic groups, study finds
In a report to Congress that is certain to generate controversy, the Federal Reserve Board says credit scores vary substantially among racial and ethnic groups, but have made credit more available for major consumer purchases such as buying a home. The Fed’s study, encompassing credit-bureau records and demographic data from a national statistical sample of 301,536 individuals, was mandated by Congress in 2003.
Credit scores are now heavily used, not only in home mortgage underwriting and pricing but also in credit cards, auto loans, employment and rental application screening, and the insurance industry. Critics have questioned the accuracy and fairness of credit-score models, charging that in some cases they are inherently biased against minority groups such as blacks and Hispanics.
After a massive research effort over several years that focused on three different credit-scoring models — including one created by Federal Reserve staff economists — the agency concluded that: ● Credit-score statistical factors and models are not biased against any particular demographic group, but are highly predictive of future payment performance. Lower scores correlate strongly with future delinquencies; higher scores are associated with good payment performance.
в—Џ Blacks and Hispanics, on average, have lower credit scores than non-Hispanic whites and Asians. в—Џ Younger individuals of all demographic groups tend to have lower credit scores on average than older individuals, in part because credit-scoring models focus on payment histories and length of credit accounts. Younger consumers generally have fewer accounts and shorter payment histories.
● The payment performances of some demographic groups are somewhat worse — or better — than their numerical scores might suggest. For example, according to the Fed, blacks, single individuals, individuals residing in lower-income or predominantly minority census tracts show consistently higher incidences of bad performance than would be predicted by their credit scores.
On the other hand, Asians, married individuals, foreign-born (particularly, recent immigrants) and those residing in higher-income census tracts consistently perform better than predicted by their credit scores. в—Џ Recent immigrants’ scores might be improved by expanding the range of creditlike accounts reported to the national credit bureaus to include rent payments and other recurring accounts.
Once in the bureaus’ files, these accounts could then be used to help compute immigrant scores, enhancing their ability to predict future payment behavior. The types of credit used by various demographic groups do not appear to be the source of differences in (payment) performance once (the) credit score is taken into account.
That finding runs counter to criticism by some consumer advocates that mortgage lenders and brokers tend to steer black and Hispanic borrowers into higher-risk, higher-cost loans — subprime adjustable-rate home loans with hefty payment jumps, for example — that increase the likelihood of default and foreclosure.
Researchers confirmed that black and Hispanic borrowers make heavier use of finance-company installment loans, and that interest rates paid by black borrowers appear to be higher in general than those paid by whites. Though most fair-lending groups have not yet reviewed the Fed’s study fully, at least one consumer advocate lambasted the report.
Calvin Bradford, formerly of the University of Minnesota’s Hubert Humphrey Institute of Public Affairs and now a fair-housing consultant, challenged the study’s statistical sampling methodology, selection of data, and failure to probe more deeply into issues of marketing of credit products to minorities.
Bradford said the Fed used an old database dating to 2003, provided by the TransUnion credit bureau, that underrepresented minorities such as black and Hispanic homeowners with mortgages, while overrepresenting whites, based on their actual proportions in the general population.
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- Published:
- 8.31.07 / 3pm
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- Bad Credit Cards
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