---
title: Banking Stability Prediction
url: https://www.ml-quant.com/papers/ssrn/4747568/
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: SSRN 4747568
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4747568
featured: 2024-03-06
citations: unknown
topic: Risk, Credit & Banking
---


# Banking Stability Prediction

The research uses the CAMELS framework and machine learning to assess the performance of major banks in top GDP countries, with the aim of predicting future performance.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4747568
- Identifier: SSRN 4747568
- Released: 2024-03-04
- First featured: Quant Letter No. 39 (2024-03-06): https://www.ml-quant.com/issues/2024-03-06/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

## Related

- [Measuring Bank Complexity Using Xai](https://www.ml-quant.com/papers/ssrn/4785689/): A machine learning technique shows a link between the complexity and opacity of banks, with complex firms seeing decreased trading activity.
- [Moderating effects of gender and family responsibilities on the relations between work–family policies and job performance](https://www.ml-quant.com/papers/doi/10-1080-09585192-2018-1505762/): Research on the Spanish banking sector shows that work-family policies indirectly improve job performance through generated well-being, with no significant influence from gender or family responsibilities.
- [The Geographic Flow of Bank Funding and Access to Credit: Branch Networks, Local Synergies, and Competition](https://www.ml-quant.com/papers/arxiv/2407.03517/): The study examines the geographic imbalance of deposits and loans, proposing a method to evaluate the impact of branch networks, market power, and scope economies on this imbalance.
- [The Not-so-Hidden Risks of ‘Hidden-to-Maturity’ Accounting: On Depositor Runs and Bank Resilience](https://www.ml-quant.com/papers/arxiv/2407.03285/): The article uses a balance sheet-based model to analyze run risk in banking systems, using the Silicon Valley Bank meltdown as a case study to show how changes in funding and asset composition can increase vulnerability.
- [Unveiling Early Warning Signals of Systemic Risks in Banks: A Recurrence Network-Based Approach](https://www.ml-quant.com/papers/arxiv/2310.10283/): The research introduces a method using high-frequency data to detect early signs of potential bank crises, proving that certain indicators can predict periods of high volatility in banking.
- [The Predictive Power of Central Bank Communication: Evidence from Mexico](https://www.ml-quant.com/papers/ssrn/4595144/): Predictive Power: The study reveals that Natural Language Processing can predict short-term interest rate decisions based on the communication strategy of Banco de México.