Institutional Affiliation: Washington University in St. Louis
|Risk and Risk Management in the Credit Card Industry|
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Using account level credit-card data from six major commercial banks from January 2009 to December 2013, we apply machine-learning techniques to combined consumer-tradeline, credit-bureau, and macroeconomic variables to predict delinquency. In addition to providing accurate measures of loss probabilities and credit risk, our models can also be used to analyze and compare risk management practices and the drivers of delinquency across the banks. We find substantial heterogeneity in risk factors, sensitivities, and predictability of delinquency across banks, implying that no single model applies to all six institutions. We measure the efficacy of a bank’s risk-management process by the percentage of delinquent accounts that a bank manages effectively, and find that efficacy also varies wid...
Published: Florentin Butaru & Qingqing Chen & Brian Clark & Sanmay Das & Andrew W. Lo & Akhtar Siddique, 2016. "Risk and risk management in the credit card industry," Journal of Banking & Finance, vol 72, pages 218-239.