Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey

Duygun, Meryem; Pasiouras, Fotios

doi:10.1016/j.ejor.2009.08.003

Cited by 663 publications

(383 citation statements)

References 121 publications

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“…Much more recent surveys such as Fethi and Pasiouras (2010) also corroborated this sort of unbalance in the literature, since their study, which covered studies employing operational research and artificial intelligence techniques to assess bank performance, corroborated the relative absence of studies analyzing either profit or revenue efficiency in banking.…”

Section: Introductionmentioning

confidence: 73%

“…The amount of research has already warranted two surveys (Berger and Humphrey, 1997;Fethi and Pasiouras, 2010). Since the publication of the latter, further empirical evidence has been made available, partly due to the substantial restructuring of the banking industries in several Western economies since the onset of the international financial crisis in 2007.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Costs, revenues and performance in Spanish banking: a comparative analysis of pre- and early crisis years

Prior

Tortosa‐Ausina

García-Alcober

et al. 2016

Spanish Journal of Finance and Accounting / Revista Española de

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Section: Introductionmentioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Costs, revenues and performance in Spanish banking: a comparative analysis of pre- and early crisis years

Prior

Tortosa‐Ausina

García-Alcober

et al. 2016

Spanish Journal of Finance and Accounting / Revista Española de

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“…For a discussion on the choice of inputs and outputs in banking applications, we refer the reader to Fethi and Pasiouras (2010). Our survey and classification of the inputs and outputs used in the literature (see Ouenniche et al 2017) along with an analysis of the balance sheet and the income statement of UK commercial banks revealed that inputs are typically chosen based on resources, costs, or financial burden, whereas outputs are typically chosen based on bank's ability to provide financial services (i.e., Loans and Deposits), generate revenue (i.e., Income and Investments) and acquire more assets (i.e., Investments).…”

Section: Empirical Studymentioning

confidence: 99%

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Ouenniche

Carrales

2018

Ann Oper Res

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Data envelopment analysis (DEA) has witnessed increasing popularity in banking studies since 1985. In this paper, we propose a new DEA-based analysis framework with a regression-based feedback mechanism, where regression analysis provides DEA with feedback that informs about the relevance of the inputs and the outputs chosen by the analyst. Unlike previous studies, the DEA models used within the proposed framework could use both inputs and outputs, only inputs, or only outputs. So far, the UK banking sector remains relatively under researched despite its crucial importance to the UK economy. We use the proposed framework to address several research questions related to both the efficiency of the UK commercial banking sector and DEA analyses with and without regression-based feedback. Empirical results suggest that, on average, the commercial banks operating in the UK-whether domestic or foreign-are yet to achieve acceptable levels of overall technical efficiency, pure technical efficiency, and scale efficiency. On the other hand, DEA analyses with and without a linear regression-based feedback mechanism seem to provide consistent findings; however, in general DEA analyses without feedback tend to over-or under-estimate efficiency scores depending on the orientation of the analyses. Furthermore, in general, a linear regression-based feedback mechanism proves effective at improving discrimination in DEA analyses unless the initial choice of inputs and outputs is well informed.Keywords Data envelopment analysis · Efficiency · UK commercial banks · DEA models without explicit inputs · DEA models without explicit outputs

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“…Since then, this method has become one of the most popular techniques for benchmarking, with applications from financial firms to public service utilities-including water utilities (Fethi and Pasiouras, 2010).…”

Section: Data Envelopment Analysis and Free Disposal Hullmentioning

confidence: 99%

The cost efficiency of water utilities: when does public ownership matter?

Pazzi

Tortosa‐Ausina

Duygun

et al. 2016

Local Government Studies

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Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey

Cited by 663 publications

References 121 publications

Costs, revenues and performance in Spanish banking: a comparative analysis of pre- and early crisis years

Costs, revenues and performance in Spanish banking: a comparative analysis of pre- and early crisis years

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

The cost efficiency of water utilities: when does public ownership matter?

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