Open Access Journal Article

A Comparative Machine Learning Survival Models Analysis for Predicting Time to Bank Failure in the US (2001-2023)

by Diego Vallarino a,*
a
Independent Researcher, Spain
*
Author to whom correspondence should be addressed.
JEA  2024, 50; 3(1), 50; https://doi.org/10.58567/jea03010007
Received: 11 June 2023 / Accepted: 9 July 2023 / Published Online: 15 March 2024
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Abstract

This study investigates the likelihood of time to bank failures in the US between 2001 and April 2023, based on data collected from the Federal Deposit Insurance Corporation's report on "Bank Failures in Brief - Summary 2001 through 2023". The dataset includes 564 instances of bank failures and several variables that may be related to the likelihood of such events, such as asset amount, deposit amount, ADR, deposit level, asset level, inflation rate, short-term interest rates, bank reserves, and GDP growth rate. We explore the efficacy of machine learning survival models in predicting bank failures and compare the performance of different models. Our findings shed light on the factors that may influence the probability of bank failures with a time perspective and provide insights for improving risk management practices in the banking industry.

Keywords: Bank bankruptcy; survival analysis; stratified hazard model; survival machine learning models;
Copyright: © 2024 by Vallarino. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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ACS Style
Vallarino, D. A Comparative Machine Learning Survival Models Analysis for Predicting Time to Bank Failure in the US (2001-2023). Journal of Economic Analysis, 2024, 3, 50. https://doi.org/10.58567/jea03010007
AMA Style
Vallarino D. A Comparative Machine Learning Survival Models Analysis for Predicting Time to Bank Failure in the US (2001-2023). Journal of Economic Analysis; 2024, 3(1):50. https://doi.org/10.58567/jea03010007
Chicago/Turabian Style
Vallarino, Diego 2024. "A Comparative Machine Learning Survival Models Analysis for Predicting Time to Bank Failure in the US (2001-2023)" Journal of Economic Analysis 3, no.1:50. https://doi.org/10.58567/jea03010007
APA style
Vallarino, D. (2024). A Comparative Machine Learning Survival Models Analysis for Predicting Time to Bank Failure in the US (2001-2023). Journal of Economic Analysis, 3(1), 50. https://doi.org/10.58567/jea03010007

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