Consumer Credit: Learning Your Customer's Default Risk from What (S)He Buys

53 Pages Posted: 16 Mar 2012

See all articles by Annette Vissing-Jorgensen

Annette Vissing-Jorgensen

Federal Reserve Board; National Bureau of Economic Research (NBER)

Date Written: April 13, 2011


Using a novel panel data set covering half a million customers of a large Mexican retail chain I study determinants of consumer credit default. I document that information about which products a customer buys provides substantial information about potential default losses on a given loan. Differences in default losses across product categories are robust to controlling for characteristics of the loan contract, demographics and more standard measures of credit risk and do not diminish substantially with how long the borrower has been a customer. The differential loss rates across product categories are driven mainly by which types of individuals buy particular products, as opposed to being product-specific features. High loss products tend to be luxuries and tend to be purchased by individuals who consume abnormally large fractions of luxuries given their income. I discuss how differences across consumers in their desire for indulgence or their degree of self-control may explain why loans to people who consume more luxuries incur higher loss rates. I propose that providers of consumer credit could benefit from adjusting credit terms (down-payment requirements, interest rates, or credit limits) as a function of product mix purchased to date, and thus that product mix should be an important component of credit scoring.

Keywords: Consumer credit, household finance, default

JEL Classification: G10, G12

Suggested Citation

Vissing-Jorgensen, Annette, Consumer Credit: Learning Your Customer's Default Risk from What (S)He Buys (April 13, 2011). Available at SSRN: or

Annette Vissing-Jorgensen (Contact Author)

Federal Reserve Board ( email )

20th Street and Constitution Avenue NW
Washington, DC 20015
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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