Efektivitas Asset And Liability Management (ALMA) pada Bank Syariah dalam Menjaga Likuiditas di tengah Ketidakpastian Kebijakan Ekonomi Global
The Effectiveness of Asset and Liability Management (ALM) in Islamic Banks in Maintaining Liquidity amid Global Economic Policy Uncertainty
DOI:
https://doi.org/10.24260/jkubs.v5i3.6965Keywords:
ALMA, Liquidity, Sharia Commercial Banks, Global Economic Policy UncertaintyAbstract
Purpose: This study aims to analyze the effect of Asset and Liability Management (ALMA) effectiveness on the liquidity of Indonesian Islamic Commercial Banks (ICBs) and examine the moderating role of Global Economic Policy Uncertainty (GEPU), while considering profitability and bank size.
Design/methodology/approach: This study employs a quantitative explanatory approach using quarterly secondary data from six ICBs in Indonesia covering 2023Q1–2026Q1, selected through purposive sampling. ALMA effectiveness is measured using a composite index comprising liquid assets, funding stability, financing–deposit balance, capital adequacy, and asset quality. Liquidity is measured using the Liquid Assets to Deposits Ratio (LADR), while profitability and bank size are represented by ROA and Total Ln, respectively. Hypotheses are tested through regression and interaction analyses.
Research Findings: ALMA has a positive and significant effect on liquidity (B = 6.706; p < 0.001). The ALMA×GEPU interaction is also positive and significant (B = 0.009; p = 0.038), indicating that the positive relationship between ALMA and liquidity tends to strengthen at higher levels of GEPU. ALMA, ROA, and SIZE are jointly significant predictors of liquidity (F = 241.681; p < 0.001; R² = 0.907). However, in the simultaneous moderation model, the ALMA×GEPU and ROA×GEPU interactions are not significant, while SIZE×GEPU cannot be estimated due to collinearity.
Contribution/Originality/Novelty: The findings highlight the relevance of strengthening ALMA in managing ICB liquidity and the need for further testing of global uncertainty effects using a more appropriate model specification.
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