---
title: Convolutional Neural Network for Enterprise Default Risk Prediction
url: https://www.ml-quant.com/papers/repec/hin-complx-5139562/
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:hin:complx:5139562
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdownloads.hindawi.com%2Fjournals%2Fcomplexity%2F2022%2F5139562.pdf%3Bh%3Drepec%3Ahin%3Acomplx%3A5139562
featured: 2023-07-12
citations: unknown
topic: Risk, Credit & Banking
---


# Convolutional Neural Network for Enterprise Default Risk Prediction

The study proposes a comprehensive metric model to address imbalanced datasets and redundant features in machine learning models for default risk prediction.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdownloads.hindawi.com%2Fjournals%2Fcomplexity%2F2022%2F5139562.pdf%3Bh%3Drepec%3Ahin%3Acomplx%3A5139562
- Identifier: RePEc:hin:complx:5139562
- Released: 2022-11-18
- 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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