Bank failure prediction models: for the developing and developed countries

Huang, Derek-Teshun; Chang, Betty; Liu, Zhien-Chia

doi:10.1007/s11135-010-9386-9

Cited by 14 publications

(21 citation statements)

References 23 publications

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“…The present study modified the Huang et al (2012) model, in which a cash flow value lower than the value of liabilities in the current year suggests bank distress. If a bank showed bank distress in year t, the value was 1; if a bank showed no bank distress in year t, the value was 0.…”

Section: Dependent Variables: Bank Failuresmentioning

confidence: 99%

“…Banks' operational system and environment also differ substantially from one nation to another and, therefore, cannot be considered equivalent. Huang, Chang, and Liu (2012) first analyzed regional groups' early warning systems for bank finances. However, the results presented only five financial ratios and did not include all countries in each regional group (instances where no data was available were excluded).…”

Section: Introductionmentioning

confidence: 99%

“…However, the results presented only five financial ratios and did not include all countries in each regional group (instances where no data was available were excluded). In addition, Huang et al (2012) did not conduct various diagnostic tests (such as, e.g., an accuracy evaluation).…”

Section: Introductionmentioning

confidence: 99%

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Cross-Country Study on the Determinants of Bank Financial Distress

Zhen-Jia-Liu

2015

Rev. adm. empres.

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Bank failures affect owners, employees, and customers, possibly causing large-scale economic distress. Thus, banks must evaluate operational risks and develop early warning systems. This study investigates bank failures in the Organization for Economic Co-operation and Development, the North America Free Trade Area (NAFTA), the Association of Southeast Asian Nations, the European Union, newly industrialized countries, the G20, and the G8. We use financial ratios to analyze and explore the appropriateness of prediction models. Results show that capital ratios, interest income compared to interest expenses, non-interest income compared to non-interest expenses, return on equity, and provisions for loan losses have significantly negative correlations with bank failure. However, loan ratios, non-performing loans, and fixed assets all have significantly positive correlations with bank failure. In addition, the accuracy of the logistic model for banks from NAFTA countries provides the best prediction accuracy regarding bank failure.KEYWORDS | Bank failure prediction, bank, distress, global, cross-country. RESUMOFalências bancárias afetam proprietários, funcionários e clientes, e têm potencial para causar crises econômicas de grande escala. Portanto, os bancos devem avaliar os riscos operacionais e desenvolver sistemas de alerta preventivo. O presente estudo investiga falências bancárias na Organização para a Cooperação e Desenvolvimento Econômico, nos países integrantes do Tratado de Livre Comér-cio da América do Norte (NAFTA, na sigla em inglês), na Associação de Nações do Sudeste Asiático, na União Europeia, em países recentemente industrializados, no G20 e no G8. Utilizamos indicadores financeiros para analisar e explorar a adequação de modelos preditivos. Os resultados demonstram que índices de capital, juros ativos comparados a despesas com juros, receitas excluindo juros comparadas a despesas excluindo juros, rentabilidade sobre o patrimônio e provisões para prejuí-zos sobre empréstimos têm correlações significantemente negativas com falências bancárias. No entanto, índices de empréstimos, créditos de liquidação duvidosa e ativos fixos têm correlações significantemente positivas com falências bancárias. Além disso, a exatidão do modelo logístico para os bancos dos países que fazem parte do NAFTA fornece melhor precisão em termos de previsão no que diz respeito à falência bancária. PALAVRAS-CHAVE | Previsão de falência bancária, bancos, crise, global, cross-country. RESUMEN Las quiebras bancarias afectan a los propietarios, empleados y clientes, y pueden causar dificultades económicas a gran escala. Por lo tanto, los bancos deben evaluar los riesgos operativos y desarrollar sistemas de alerta temprana. Este estudio investiga las quiebras bancarias en la Organización para la RAE-Revista de Administração de Empresas | FGV-EAESP

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Section: Dependent Variables: Bank Failuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cross-Country Study on the Determinants of Bank Financial Distress

Zhen-Jia-Liu

2015

Rev. adm. empres.

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“…This process, which fosters industrial development and economic growth, separates banks from other businesses. When banks collapse because of mismanagement, it affects investors and employees, eliminating the rights of customers, negatively affecting other industries, and potentially leading to international financial distress and destabilized economies (Huang et al, [1]).…”

Section: Introductionmentioning

confidence: 99%

Bank Failure Prediction in Relation to the Business Life Cycle

Wang¹,

Yang²,

Liu³

2019

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The results suggest that the capital ratio, loan ratio, non-performing loans, provisions for loan losses, fixed assets, return of equity, ratio of interest income to interest expenses, and ratio of non-interest income to non-interest expenses all had different correlations to the financial distress experienced by banks that were at a business life cycle stage. The logistic model employed in this study for predicting bank failure explains most of the banking trends in NIC banks at the declining stage. The accuracy of G8 banks at the growth stage performed well, whereas NIC banks at the declining stage performed poorly.

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“…Thus, the collapse of banks, often caused by mismanagement or the economic environment, negatively affects depositor rights and other industries, can induce international financial distress and destabilize economic development. Consequently, evaluating bank operations and establishing an early warning system are a top priority for global financial authority (Huang et al, 2012).…”

Section: Introductionmentioning

confidence: 99%