Exploring Population Drift on Consumer Credit Behavioral Scoring

Dimitris Nikolaidis, Michael Doumpos () and Constantin Zopounidis ()
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Dimitris Nikolaidis: Technical University of Crete
Michael Doumpos: Technical University of Crete
Constantin Zopounidis: Technical University of Crete

A chapter in Operational Research in Business and Economics, 2017, pp 145-165 from Springer

Abstract: Abstract Behavioral credit scoring models are a specific kind of credit scoring models, where time-evolving data about delinquency pattern, outstanding amounts, and account activity, is used. These data have a dynamic nature as they evolve over time in accordance with the economic environment. On the other hand, scoring models are usually static, implicitly assuming that the relationship between the performance characteristics and the subsequent performance of a customer will be the same under the current situation as it was when the information on which the scorecard was built was collected, no matter what economic changes have occurred in that period. In this study we investigate how this assumption affects the predictive power of behavioral scoring models, using a large data set from Greece, where consumer credit has been heavily affected by the economic crisis that hit the country since 2009.

Keywords: Behavioral credit scoring; Consumer credit; Population drift; Risk management (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-319-33003-7_7

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DOI: 10.1007/978-3-319-33003-7_7

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