Risk and Risk Management in the Credit Card Industry

Florentin Butaru, QingQing Chen, Brian Clark, Sanmay Das, Andrew Lo () and Akhtar Siddique

No 21305, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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 widely across institutions. These results suggest the need for a more customized approached to the supervision and regulation of financial institutions, in which capital ratios, loss reserves, and other parameters are specified individually for each institution according to its credit-risk model exposures and forecasts.

JEL-codes: D12 D14 D18 E21 E51 G01 G17 G21 (search for similar items in EconPapers)
Date: 2015-06
New Economics Papers: this item is included in nep-mac and nep-rmg
Note: AP ME
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Citations: View citations in EconPapers (3)

Published as 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.

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