---
title: Machine Learning in Credit Scoring
url: https://www.ml-quant.com/papers/repec/eee-aosoci-v-113-y-2024-i-c-s0361368224000278/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:aosoci:v:113:y:2024:i:c:s0361368224000278
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0361368224000278%3Bh%3Drepec%3Aeee%3Aaosoci%3Av%3A113%3Ay%3A2024%3Ai%3Ac%3As0361368224000278
featured: 2024-12-18
citations: unknown
topic: Risk, Credit & Banking
---


# Machine Learning in Credit Scoring

Research in a Chinese internet company shows machine learning credit scoring models prioritize data trails over default risk, reducing human experts' role to machine learning facilitators.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0361368224000278%3Bh%3Drepec%3Aeee%3Aaosoci%3Av%3A113%3Ay%3A2024%3Ai%3Ac%3As0361368224000278
- Identifier: RePEc:eee:aosoci:v:113:y:2024:i:c:s0361368224000278
- Released: 2024-12-18
- First featured: Quant Letter No. 79 (2024-12-18): https://www.ml-quant.com/issues/2024-12-18/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

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