A Modified Network DEA Model for Bank Efficiency Analysis Considering Risk Factors

Fatemeh Fattahi (), Ali Hadi (), Mohammad Afzalinejad () and Farhad Hosseinzadeh Lotfi ()
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Fatemeh Fattahi: Kharazmi University
Ali Hadi: Islamic Azad University
Mohammad Afzalinejad: Tafresh University
Farhad Hosseinzadeh Lotfi: Islamic Azad University

SN Operations Research Forum, 2024, vol. 5, issue 4, 1-24

Abstract: Abstract The banking industry plays a major role in the economy and financial structure of a country. Assessing the efficiency of banks is a complicated issue, and there are different points of view about the nature of this business. Bank managers look for an appropriate method that includes various aspects and provides realistic performance evaluations. Risk is very important in financial management, and the trade-off between deposit sustainability and bank loans should be considered in the assessment. Previous data envelopment analysis (DEA) models ignored the sustainability of bank deposits (the role of risk) when assessing their effectiveness. In this document, liquidity risk is reviewed to obtain a better assessment of operations and risk management. In the proposed model, unlike other existing models, risk calculation is performed within the data envelopment analysis model to integrate the three aspects of bank operation, namely production, intermediation, and profitability, as sub-processes in a three-stage network. The sustainability factor is assessed by conditional value at risk (CVaR) and is included in the DEA model to obtain a more comprehensive assessment of banks’ performance. The new model applies a stricter assessment and has a high degree of differentiation. Identifying sources of inefficiency is another benefit of the model, which is obtained by providing stage efficiency scores. The paper evaluates 40 branches of an Iranian private bank using the proposed method and shows how the new method can provide more information regarding banks’ performance.

Keywords: Conditional value at risk; Network data envelopment analysis; Efficiency; Sustainability; Banking (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s43069-024-00379-9

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