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Credit where none is due? Authorized user account status and \"piggybacking credit\"

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Abstract

An \"authorized user\" is a person who is permitted by a revolving account holder to use an account without being legally liable for any charges incurred. The Federal Reserve's Regulation B, which implements the 1974 Equal Credit Opportunity Act, requires that information on spousal authorized user accounts be reported to the credit bureaus and considered when lenders evaluate credit history. Since creditors generally furnish to the credit bureaus information on all authorized user accounts, without indicating which are spouses and which are not, credit scoring modelers cannot distinguish spousal from non-spousal authorized user accounts. This effectively requires that all authorized user accounts receive similar treatment. Consequently, becoming an authorized user on an old account with a good payment history, may improve an individual's credit score, potentially increasing access to credit or reducing borrowing costs. As a result, the practice of \"piggybacking credit\" has developed. In a piggybacking arrangement, an individual pays a fee to be added as an authorized user on an account to \"rent\" the account's credit history. This paper provides the first comprehensive look at authorized user accounts in individual credit records and how their importance differs across demographic groups. Our analysis suggests that piggybacking credit can materially improve credit scores, particularly for individuals with thin or short credit histories. We also evaluate the effect that eliminating authorized user accounts from credit scoring models would have on individual credit scores. Our results suggest that removing this information has relatively little effect on credit scores, but may reduce model predictiveness.

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  • Robert B. Avery & Kenneth P. Brevoort & Glenn B. Canner, 2010. "Credit where none is due? Authorized user account status and \"piggybacking credit\"," Finance and Economics Discussion Series 2010-23, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2010-23
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    1. Pagano, Marco & Jappelli, Tullio, 1993. "Information Sharing in Credit Markets," Journal of Finance, American Finance Association, vol. 48(5), pages 1693-1718, December.
    2. Wojtek J. Krzanowski & David J. Hand, 2011. "Testing the difference between two Kolmogorov--Smirnov values in the context of receiver operating characteristic curves," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 437-450, October.
    3. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
    4. Eric Rosenberg & Alan Gleit, 1994. "Quantitative Methods in Credit Management: A Survey," Operations Research, INFORMS, vol. 42(4), pages 589-613, August.
    5. Kenneth P. Brevoort & Cheryl R. Cooper, 2013. "Foreclosure's Wake: The Credit Experiences of Individuals Following Foreclosure," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 41(4), pages 747-792, December.
    6. Padilla, A. Jorge & Pagano, Marco, 2000. "Sharing default information as a borrower discipline device," European Economic Review, Elsevier, vol. 44(10), pages 1951-1980, December.
    7. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
    8. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    9. Robert B. Avery & Paul S. Calem & Glenn B. Canner, 2003. "An overview of consumer data and credit reporting," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), vol. 89(Feb), pages 47-73, February.
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    Keywords

    Credit scoring systems; Consumer credit;

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