Abstract
Loan default risk prediction is necessary in credit risk assessment, as it helps financing institutions and investors make decisions. However, existing prediction models focus more on using individual classifiers to obtain higher prediction accuracy, which is far from the core purpose of business (i.e., maximizing profit) and leaves opportunities to explore profit-oriented and interpretable weighting models. This study proposes a profit-oriented weighting model for loan default prediction. The model consists of three stages: constructing multiple profit-oriented sub-classifiers, determining profit-oriented weight coefficients, and providing interpretable analysis. Five lending datasets are examined based on accuracy and profit-based metrics. The empirical results demonstrate that the proposed weighting prediction system helps lenders achieve higher profits and provides concise and intuitive interpretability. Thus, it can help practitioners make better decisions and manage risk.
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The data that support the findings of this study are available from the corresponding author upon request.
Change history
21 March 2024
A Correction to this paper has been published: https://doi.org/10.1007/s10479-024-05952-3
Notes
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Acknowledgements
This work was supported by Major Program of National Fund of Philosophy and Social Science of China (Grant No. 17ZDA093).
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This work was supported by the Major Program of National Fund of Philosophy and Social Science of China (Grant numbers [17ZDA093]).
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Cui, H., Zhang, L., Yang, H. et al. Maximizing the lender’s profit: profit-oriented loan default prediction based on a weighting model. Ann Oper Res (2024). https://doi.org/10.1007/s10479-024-05912-x
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DOI: https://doi.org/10.1007/s10479-024-05912-x