---
title: Artificial Neural Networks Enhance Credit Risk Prediction
url: https://www.ml-quant.com/papers/repec/taf-oaefxx-v-11-y-2023-i-1-p-2210916/
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:taf:oaefxx:v:11:y:2023:i:1:p:2210916
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F23322039.2023.2210916%3Bh%3Drepec%3Ataf%3Aoaefxx%3Av%3A11%3Ay%3A2023%3Ai%3A1%3Ap%3A2210916
featured: 2023-07-12
citations: unknown
topic: Risk, Credit & Banking
---


# Artificial Neural Networks Enhance Credit Risk Prediction

The study reveals that machine learning is superior to logistic regression in predicting company bankruptcy, and its predictive accuracy increases when factors like changes in operating expenditure are included in the model.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F23322039.2023.2210916%3Bh%3Drepec%3Ataf%3Aoaefxx%3Av%3A11%3Ay%3A2023%3Ai%3A1%3Ap%3A2210916
- Identifier: RePEc:taf:oaefxx:v:11:y:2023:i:1:p:2210916
- Released: 2023-07-12
- First featured: Quant Letter No. 7 (2023-07-12): https://www.ml-quant.com/issues/2023-07-12/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

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