Consumer Credit Scoring
After presenting the main issues in consumer credit market and introducing the issue of credit scorecards, I have used statistical modeling to predict the default probabilities of applicants in a dataset of consumer loans. I have found evidence for the superior accuracy of complex non-linear estimations. In particular, the bagging model offers better results than the traditional tree and logit estimations. The proposed statistical scorecard offers a 60 percent improvement over the baseline model. Lastly, this paper argues that the management must establish a decisional probability threshold in accordance with its propensity for risk. A higher threshold requires a greater promotional effort, although the increased costs may be compensated by a more efficient communication with clients and by more flexible contractual clauses.
Volume (Year): (2011)
Issue (Month): 3 (September)
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References listed on IDEAS
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- Adrian Blundell-Wignall & Paul Atkinson, 2010. "Thinking beyond Basel III: Necessary Solutions for Capital and Liquidity," OECD Journal: Financial Market Trends, OECD Publishing, vol. 2010(1), pages 9-33.
- Rinaldi, Laura & Sanchis-Arellano, Alicia, 2006. "Household debt sustainability: what explains household non-performing loans? An empirical analysis," Working Paper Series 0570, European Central Bank.
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