Bank Failures: Review and Comparison of Prediction Models

Citterio, Alberto

doi:10.2139/ssrn.3719997

Cited by 5 publications

(1 citation statement)

References 137 publications

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“…We select bank-specific measures following the CAMEL(S) [12] supervisory rating system, which is widely used in related studies since CAMEL(S)-indicators provide accurate predictions of bank distress (e.g. Gal an, 2021;Citterio, 2020). We include a bank's capital ratio, asset quality, cost-to-income ratio (CIR), net interest margin (NIM) and liquid assets.…”

Section: Data and Sourcesmentioning

confidence: 99%

The impact of market concentration and market power on banking stability – evidence from Europe

Herwald,

Voigt,

Uhde

2024

JRF

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PurposeAcademic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.Design/methodology/approachUsing data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.FindingsOur analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.Originality/valueOur results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

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Section: Data and Sourcesmentioning

confidence: 99%

The impact of market concentration and market power on banking stability – evidence from Europe

Herwald,

Voigt,

Uhde

2024

JRF

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Environmental, social, and governance (ESG) and artificial intelligence in finance: State-of-the-art and research takeaways

Lim

2024

Artif Intell Rev

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The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation focuses on three primary research questions: the main research themes concerning ESG and AI in finance, the evolution of research intensity and interest in these areas, and the application and evolution of AI techniques specifically in research studies within the ESG and AI in finance domain. Eight archetypical research domains were identified: (i) Trading and Investment, (ii) ESG Disclosure, Measurement and Governance, (iii) Firm Governance, (iv) Financial Markets and Instruments, (v) Risk Management, (vi) Forecasting and Valuation, (vii) Data, and (viii) Responsible Use of AI. Distinctive AI techniques were found to be employed across these archetypes. The study contributes to consolidating knowledge on the intersection of ESG, AI, and finance, offering an ontological inquiry and key takeaways for practitioners and researchers. Important insights include the popularity and crowding of the Trading and Investment domain, the growth potential of the Data archetype, and the high potential of Responsible Use of AI, despite its low publication count. By understanding the nuances of different research archetypes, researchers and practitioners can better navigate this complex landscape and contribute to a more sustainable and responsible financial sector.

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Environmental, Social, and Governance (ESG) and Artificial Intelligence in Finance: State-of-the-Art and Research Takeaways

Lim

2023

Preprint

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The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation centers around three research questions: key research themes for ESG and AI in finance, research intensity and interest evolution, and the use and progression of AI techniques within these themes. Eight archetypical research domains were identified: (i) Trading and Investment, (ii) ESG Disclosure, Measurement and Governance, (iii) Firm Governance, (iv) Financial Markets and Instruments, (v) Risk Management, (vi) Forecasting and Valuation, (vii) Data, and (viii) Responsible Use of AI. Distinctive AI techniques were found to be employed across these archetypes. The study contributes to consolidating knowledge on the intersection of ESG, AI, and finance, offering an ontological inquiry and key takeaways for practitioners and researchers. Important insights include the popularity and crowding of the Trading and Investment domain, the growth potential of the Data archetype, and the high potential of Responsible Use of AI, despite its low publication count. By understanding the nuances of different research archetypes, researchers and practitioners can better navigate this complex landscape and contribute to a more sustainable and responsible financial sector.

show abstract

Bank Failures: Review and Comparison of Prediction Models

Cited by 5 publications

References 137 publications

The impact of market concentration and market power on banking stability – evidence from Europe

The impact of market concentration and market power on banking stability – evidence from Europe

Environmental, social, and governance (ESG) and artificial intelligence in finance: State-of-the-art and research takeaways

Environmental, Social, and Governance (ESG) and Artificial Intelligence in Finance: State-of-the-Art and Research Takeaways

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