The Illusion of Improvement: Reject Inference Strategies in Credit Scoring
Reject inference methods are widely used to mitigate survival bias in credit scoring, yet their effectiveness remains poorly understood. We systematically evaluate several such methods and uncover a structural failure mode: in a natural retraining cycle, models whose accuracy improves while recall collapses create an illusion of improvement that leads practitioners to believe the system is getting better when, in fact, its rejection quality---the ability to correctly screen out defaulters---is deteriorating. We then propose a controlled exploration strategy that breaks the feedback loop without statistical assumptions: the lender deliberately approves a fraction of rejected applicants and...
| Authors | Bruno Scarone, Ricardo Baeza-Yates |
|---|---|
| Primary category | cs.LG |
| Published | 16 June 2026 |
| Last updated at source | 18 September 2026 |
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