Addressing Vagueness and Uncertainty in the Banking Industry: Combining Fuzzy Modulatory Data Envelopment Analysis and Fuzzy Multivariate Regression

Wanke, Peter; Tan, Yong; Walheer, Barnabé

doi:10.1111/exsy.70249

Article (Scientific journals)

Addressing Vagueness and Uncertainty in the Banking Industry: Combining Fuzzy Modulatory Data Envelopment Analysis and Fuzzy Multivariate Regression

Wanke, Peter; Tan, Yong; Walheer, Barnabé

2026 • In Expert Systems, 43 (5)

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https://hdl.handle.net/2268/346170

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10.1111/exsy.70249

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Keywords :

Chinese banks; data envelopment analysis; financial distress; fuzzy multivariate regression; fuzzy-modulatory slack-based measurement; risk management; Banking industry; Chinese bank; Data envelopment; Financial distress; Financial health; Fuzzy multivariate regression; Fuzzy-modulatory slack-based measurement; Multivariate regression; Risks management; Vagueness and uncertainty; Control and Systems Engineering; Theoretical Computer Science; Computational Theory and Mathematics; Artificial Intelligence

Abstract :

[en] This study develops a novel two-stage framework to evaluate financial health, distress and liquidity traps in the banking industry by integrating a Fuzzy Modulatory Data Envelopment Analysis model with a Fuzzy Multivariate Lognormal Regression. The methodology incorporates fuzzy set theory with alpha-cuts to capture vagueness and uncertainty in inputs, outputs and intermediate variables, addressing inherent data imprecision in financial systems. An empirical analysis of 93 Chinese banks (2014–2023) reveals key drivers of inefficiency, including labour costs, capital adequacy and market concentration, while highlighting the moderating effects of competition and regulatory measures. Results demonstrate improved efficiency trends and convergence in operational practices, influenced by regulatory compliance and macroeconomic policies. The framework further identifies contextual factors—such as the Herfindahl–Hirschman Index and CAMELS ratings—impacting inefficiencies under varying levels of uncertainty, offering a comprehensive risk management and policy evaluation tool. This research contributes to operational research by bridging gaps in banking efficiency analysis and providing actionable insights for enhancing financial stability and resilience under uncertain market conditions.

Disciplines :

Quantitative methods in economics & management

Author, co-author :

Wanke, Peter; EBAPE, Fundação Getúlio Vargas, Rio de Janeiro, Brazil

Tan, Yong ; School of Management, University of Bradford, Bradford, United Kingdom

Walheer, Barnabé ; Université de Liège - ULiège > HEC Liège : UER > UER Economie : Microéconométrie et économétrie appliquée

Language :

English

Title :

Addressing Vagueness and Uncertainty in the Banking Industry: Combining Fuzzy Modulatory Data Envelopment Analysis and Fuzzy Multivariate Regression

Publication date :

May 2026

Journal title :

Expert Systems

ISSN :

0266-4720

eISSN :

1468-0394

Publisher :

John Wiley and Sons Inc

Volume :

Issue :

Peer reviewed :

Editorial Reviewed verified by ORBi

Additional URL :

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.70249

Funders :

F.R.S.-FNRS - Fonds de la Recherche Scientifique

Funding text :

This work was supported by the Universit\u00E9 de Li\u00E8ge (Research Credit), Fonds De La Recherche Scientifique (FNRS, J.0193.23).

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since 18 June 2026

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