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Muhammad Zaki As Shafi MT
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Economics, Econometrics & Finance

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Early Warning System for Islamic Banks: a Panel Logit Approach to Financial Distress in Indonesia Muhammad Zaki As Shafi MT
Journal Of Economic Cluster Vol. 2 No. 1 (2025): JoEC: Journal of Economic Cluster
Publisher : CV. Era Digital Nusantara

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Abstract

This study uses a quantitative approach with a causal-comparative design. The population is all Islamic Banks (BUS) in Indonesia, with a sample of 10 BUS selected through purposive sampling during the 2019–2024 period, resulting in 60 panel data observation units. The analysis technique used is Panel Data Logistic Regression to estimate the probability of Financial Distress. Model validation is carried out through a classification matrix and Area Under the Curve (AUC). The results of the study indicate that the model has very strong discriminatory power with an overall prediction accuracy reaching 100% (Nagelkerke R Square = 1.000). The regression coefficients indicate that Financing Risk (NPF) and Operational Inefficiency (BOPO) have a significant positive effect on the probability of Financial Distress. Meanwhile, Bank Size (SIZE) also shows a positive effect that rejects the 'Too Big to Fail' hypothesis, and Liquidity (FDR) shows a negative effect, functioning as a buffer for profitability. This study concludes that NPF and BOPO are the most critical early warning indicators, and the Logit model built can be a valid and specific Early Warning System for BUS regulators and management.
Determinants of Financial Distress in Islamic Banks: Does Firm Size Matter? Muhammad Zaki As Shafi MT
Journal Of Economic Cluster Vol. 1 No. 2 (2024): JoEC: Journal of Economic Cluster
Publisher : CV. Era Digital Nusantara

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Abstract

This study examines the effects of Non-Performing Financing (NPF), Financing to Deposit Ratio (FDR), and Operating Expenses to Operating Income (BOPO) on Financial Distress, with Firm Size as a moderating variable, in Indonesian Sharia Commercial Banks from 2019 to 2023. Using panel data from 10 banks analyzed using the Random Effects Model (REM), the findings reveal that only FDR significantly affects Financial Distress. A key discovery is that Firm Size significantly moderates (weakens) the negative impact of FDR on Financial Distress, providing empirical support for the "Too Big to Fail" theory within the Islamic banking ecosystem. Conversely, NPF and BOPO showed no significant effects, suggesting that capital buffers and restructuring policies effectively mitigated financing risks and inefficiencies during the pandemic. Theoretically, this research contributes to the international Islamic finance literature by demonstrating that asset size is a more critical determinant of liquidity resilience than credit risk in distressed conditions. The global policy implications underscore the necessity for differential regulatory standards for smaller-scale Islamic banks to prevent systemic risks in emerging markets.
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