---
title: Bank Failure Prediction
url: https://www.ml-quant.com/papers/repec/bba-j00001-v-3-y-2024-i-1-p-129-144-d-169/
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:bba:j00001:v:3:y:2024:i:1:p:129-144:d:169
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.anserpress.org%2Fjournal%2Fjea%2F3%2F1%2F50%2Fpdf%3Bh%3Drepec%3Abba%3Aj00001%3Av%3A3%3Ay%3A2024%3Ai%3A1%3Ap%3A129-144%3Ad%3A169
featured: 2025-10-24
citations: unknown
topic: Risk, Credit & Banking
---


# Bank Failure Prediction

The study uses machine learning survival models to predict US bank failures, offering insights to enhance risk management in the banking sector.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.anserpress.org%2Fjournal%2Fjea%2F3%2F1%2F50%2Fpdf%3Bh%3Drepec%3Abba%3Aj00001%3Av%3A3%3Ay%3A2024%3Ai%3A1%3Ap%3A129-144%3Ad%3A169
- Identifier: RePEc:bba:j00001:v:3:y:2024:i:1:p:129-144:d:169
- Released: 2024-03-02
- First featured: Quant Letter No. 116 (2025-10-24): https://www.ml-quant.com/issues/2025-10-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

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