Devos, A., Dhondt, J., Stripling, E., Baesens, B., van den Broucke, S. and Sukhatme, G. (2018) Profit Maximizing Logistic Regression Modeling for Credit Scoring. Proceedings of the 2018 IEEE Data Science Workshop (DSW), Lausanne, Switzerland, 4-6 June 2018, 125-129.
https://doi.org/10.1109/DSW.2018.8439113

has been cited by the following article:

• TITLE: Profitability vs. Credit Score Models—A New Approach to Short Term Credit in the UK

  AUTHORS: Marko Sjoblom, Alessio Castello, Gregory Gadzinski

  KEYWORDS: Financial Innovation, Profitability Model, Overdraft, Credit Scores

  JOURNAL NAME: Theoretical Economics Letters, Vol.9 No.4, April 30, 2019

  ABSTRACT: The profitability lending model was initially discussed by Eisenbeis [1] who suggested that it might be possible to build a lending model that prevailed the traditional scorecard models. In this paper, we study a unique dataset from a personal loan company based in the United Kingdom, which offered overdraft-style short-term loans to individuals with low and high credit scores during the last few years. Our results conclude that credit score does not significantly impact profitability in the overdraft market. Moreover, we argue that, assuming a good understanding of low credit score individuals, a business model that grants loans to these “new” customers is as sustainable and commercially viable as lending to higher credit profile applicants.