Measuring Islamic Banking resilience: A case study of Nusa Tenggara Barat Province, Indonesia

Dimas Bagus Wiranatakusuma () and Anggi Aprizal ()

Economic Journal of Emerging Markets, 2025, vol. 17, issue 2, 191-207

Abstract: Purpose — Islamic banks in Nusa Tenggara Barat (NTB) province have experienced positive developments in assets, branches, and financing. This study aims to measure the resilience of Islamic banking in NTB using a composite bank variable and to determine how effectively the institution manages and absorbs various risks. Method — The data used consisted of monthly data from 2010 to 2023, covering several banking variables, including the Financing to Deposits Ratio (FDR), Non-Performing Financing (NPF), Bank Size (BS), and Third-Party Fund (TPF). The analysis method employed in this study was the early warning system (EWS), utilising a non-parametric signal extraction approach. Findings — All selected banking variables are used to measure the resilience of Islamic banking in NTB through the composite index of bank (CIB). The signal extraction method provides optimal thresholds for each selected banking variable and for the composite index (CIB). Visualisation results show the interval values that can absorb risk and maintain the resilience of Islamic banking as follows: (1) FDR between 81% and 102%; (2) NPF between 1.29% and 1.89%; (3) BS between 3.79% and 4.59%; (4) TPF between 4.16% and 4.58%; and (5) CIB between 10.66 and 28.14.Implications — Assessing the resilience of Islamic banking in NTB involves identifying key banking variables to pinpoint sources of risk exposure, determining the optimal time horizon for policy interventions, and setting appropriate thresholds for the surveillance mechanism.Originality — Currently, the resilience of Islamic banks at the provincial level has not been widely studied, particularly in NTB Province, where there has been a notable increase in Islamic banking offices and assets.

Keywords: Islamic banking; resilience; optimal threshold; optimal time horizon; early warning system approach (search for similar items in EconPapers)
Date: 2025
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