Robust Credit-Stress Prediction Under Borrower Behavioural Drift: An Explainable Framework for MSME Lending

Authors

  • D Ajay Kumar Author

DOI:

https://doi.org/10.48047/p9pxn847

Keywords:

MSME lending, credit stress, borrower behaviour, concept drift, robust prediction, explainable AI, temporal validation.

Abstract

MSME borrowers operate in changing markets where payment cycles, cash conversion, input costs, and account behaviour can evolve after loan origination. A risk model trained on historical patterns may therefore mis-rank emerging stress even when its input fields remain unchanged. This paper proposes an explainable robust credit-stress 

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Published

15.06.2026

Issue

Vol. 14 No. 4 (2024): volume 14 issue 4(2024)

Section

Articles

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How to Cite

Robust Credit-Stress Prediction Under Borrower Behavioural Drift: An Explainable Framework for MSME Lending. (2026). International Journal of Information and Electronics Engineering, 14(4), 172-177. https://doi.org/10.48047/p9pxn847