Consumer Credit Scoring
AbstractAfter 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.
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Bibliographic InfoArticle provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.
Volume (Year): (2011)
Issue (Month): 3 (September)
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More information through EDIRC
credit market; prudential regulation; statistical scorecards; logit; bagging estimations;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
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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.
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