Issue #2 (Volume 21 2026)

Type of the article: Research Article

Abstract
This study examines the impact of exchange rate fluctuations on banking and financial service indices in India. To validate this, five exchange rates are considered based on their relative share in the total foreign remittance inflows to India, viz., Arabian Dirham (AED/INR), Great Britain Pound (GBP/INR), Saudi Riyal (SAR/INR), Singapore Dollar (SGD/INR), and US Dollar (USD/INR). The study includes daily data of a decade (2015–2025), and employs various econometric techniques such as ADF test, Johansen cointegration, Vector Error Correction Model (VECM), and Impulse Response Function (IRF) for the analysis. The Johansen cointegration test indicates a long-run relationship between exchange rates and both the sectoral indices, as the probabilities are less than 0.05. The VECM analysis for both the Nifty Bank and Nifty FinServ identified USD/INR (2,308.66; 2,257.58) and SAR/INR (373.25; 360.73) as the dominant long-term drivers, whereas AED/INR (–2,671.406; –2,608.011) acts as a persistent structural anchor with a negative influence. In the short run, shocks in USD/INR and SGD/INR generate immediate positive effects, whereas volatility in AED/INR and SAR/INR leads to temporary negative deviations before the system converges back to the equilibrium. The impulse response function indicates that exchange rate shocks have temporary effects on both the indices, which dissipate quickly, reflecting rapid market adjustment and overall efficiency. The findings of this study will help policymakers to improve the exchange rate risk monitoring system and executives in banks and financial institutions to formulate their hedging strategies. For investors and portfolio managers, the findings suggest that currency movements can serve as early indicators of market fluctuations, thereby supporting more informed investment decisions.

Type of the article: Research Article

Abstract
Sustaining employee engagement has become essential for the operational efficiency and service quality of Indian public sector banks, particularly as Generation Y employees increasingly constitute a major share of the workforce. This study aims to empirically validate a gender-moderated structural model of employee engagement among Generation Y employees in Indian public sector banks. Data were collected from 223 Generation Y employees across public-sector banks in India, using a combination of a paper-based questionnaire and an online Google Forms survey. Variance-based structural equation modelling was used to assess the measurement and structural models, while multi-group analysis explored gender-specific differences in the hypothesized paths. Six significant antecedents of employee engagement were identified: Corporate Social Responsibility, Dispositional Characteristics, Psychological Availability, Psychological Safety, Perceived Supervisor Support and Transformational Leadership, and Social and Interpersonal Relationships. Engagement positively affected Organizational Citizenship Behavior and Task Performance, and mediated all antecedent–outcome relationships. Gender-based differences emerged, with Corporate Social Responsibility and Dispositional Characteristics more influential for women, while Fit Perceptions and Distributive Justice showed stronger effects for men. The study contributes to the banking literature by offering a multidimensional, empirically tested engagement model and demonstrating gender’s moderating role.

Type of the article: Research Article

Abstract
Fraud remains a pervasive challenge undermining financial integrity and stability in the banking sector, particularly in developing economies. This study investigates the determinants of fraud detection effectiveness in Indonesian Regional Development Banks (RDBs), focusing on auditor competency, internal control effectiveness, risk-based internal audit, risk management processes, and information technology utilization. The study population consisted of internal auditors, managers, and audit committee members at Indonesian Regional Development Banks. Using a quantitative approach with 204 survey responses analyzed through Partial Least Squares-Structural Equation Modeling (PLS-SEM), the results show that all five factors have a significant positive effect on fraud detection (R2 = 0.554). Risk-based internal audit demonstrates the strongest influence (sig 0.000 < 0.05), followed by risk management processes (sig 0.003 < 0.05), information technology (sig 0.002 < 0.05), internal control effectiveness (sig 0.001 < 0.05), and auditor competency (sig 0.017 < 0.05). The results reveal that all five factors significantly enhance auditors’ ability to detect fraud. These findings indicate that governance mechanisms and digital capabilities jointly enhance fraud detection effectiveness in RDBs.

Acknowledgment
The authors would like to thank the Universitas Sumatera Utara, Indonesia, especially the Research Institute, for its support and the Ministry of Education and Research through the Directorate of Research, Technology, and Community Service program for providing intellectual assistance and funding for this project in the PMDSU grant (number: 83/UN5.4.10.K/PT.01.03/KP-DRTPM/2025).

Type of the article: Research Article

Abstract
Central bank independence is widely recognized as a precondition for launching inflation targeting, but there is no empirical support for this. While actual independence of monetary institutions is key for the effective implementation of this monetary regime, formal reforms have been implemented extremely unevenly both over time and across countries. Legal origins may affect different institutional paths of central bank independence strengthening during the adoption of inflation targeting across countries. Applying a t-test, panel regression, and difference-in-difference based event-study analysis, we show a strong statistically significant distance between levels of central bank independence across Common Law and Civil Law countries with inflation targeting. Civil Law countries perform with higher central bank independence; they are more likely to strengthen it before inflation targeting launch and continue to reform the central bank’s legislation toward greater autonomy after the introduction of this monetary regime. These results confirm that Legal origins matter for central bank independence. More formally oriented Civil Law coexists with relevant legislation changes. While less formally oriented Common Law may not require changes in legislation to implement a monetary regime grounded on central bank independence, in essence. Such results help explain weak empirical arguments for strengthening central bank independence as a precondition for inflation targeting, given the structural heterogeneity of countries determined by legal tradition.

Type of the article: Research Article

Abstract
Bank profitability, as measured by return on equity (ROE), may arise from different combinations of operating efficiency, risk costs, and capital intensity, making headline profitability comparisons potentially misleading. Understanding the sources of cross-bank profitability differences is therefore important for performance evaluation and supervisory interpretation.
The purpose of this study is to assess how accounting-based performance components explain cross-bank variation in ROE among Armenian banks using year-end 2023 IFRS data and a Shapley variance decomposition applied to these components. The empirical analysis uses published IFRS financial statements for ten banks representing approximately 75% of total sector assets. ROE is mapped into cost efficiency, leverage, income margins, and provisioning using an accounting identity, and a Shapley variance decomposition is applied to attribute cross-bank variation in pre-tax ROE, excluding tax effects from variance attribution.
The results indicate that cost efficiency accounts for 49.6% of cross-bank pre-tax ROE variation in 2023, followed by leverage at 22.6% and provisioning at 14.8%, while income-related components jointly account for the remaining 13%. Importantly, these variance shares reflect both the role of each component in the accounting transmission from income to profitability and the magnitude of its cross-sectional variation across banks. These results describe the structure of cross-bank profitability differences in the Armenian banking sector in 2023 and support transparent peer comparison and consistent supervisory interpretation of bank profitability. All variance shares are reported for pre-tax ROE to improve comparability by abstracting from institution-specific tax effects.

Type of the article: Research Article

Abstract
This study examines the post-decision announcements of the National Bank of Ukraine (NBU) during the pre-war and wartime periods from 2018 to 2025, focusing on changes in communication complexity and their subsequent impact on the anchoring of household inflation expectations. Based on various readability measures, we document a significant increase in the linguistic complexity of NBU communications during the war. For example, the Flesch-Kincaid Grade Level index indicates that the number of years of schooling required to understand NBU announcements increased by approximately one additional year. Despite these changes, we find no statistically significant effect on the gap between household inflation expectations and the NBU’s inflation forecast. At the same time, the expectations gap narrowed substantially during the war period, likely due to the convergence of households and NBU predictions under shock conditions. Moreover, the gap continued to narrow as inflation pressures eased. Our econometric analysis relies on dynamic specifications with robust inference to account for persistence, serial correlation, and structural breaks associated with the full-scale invasion. The findings contribute to the literature on central bank communication by providing rare wartime evidence from a small open economy, highlighting the limits of textual complexity as a policy tool for shaping household expectations.

Type of the article: Research Article

Abstract
The study analyzes the role of the Funding Gap (FGAP) as a dynamic structural liquidity indicator that influences bank financial stability in emerging markets, particularly amid heightened post-COVID-19 financial volatility. It aims to forecast banking stability by integrating advanced econometric and machine-learning techniques using a balanced panel dataset of 63 commercial banks from six ASEAN countries over the period 2010–2023. The methodological framework combines Ridge regression for variable selection, Particle Swarm Optimization (PSO) for hyperparameter tuning, and SHapley Additive exPlanations (SHAP) for interpretability within a Gradient Boosting model. The PSO-optimized specification achieves an R2 of 92.2%, substantially outperforming traditional fixed-effects and random-effects regressions. Empirical results indicate that persistent negative FGAP values significantly reduce Z-scores, confirming that structural liquidity imbalances constitute a key transmission channel from funding stress to systemic fragility. The analysis further reveals the moderating role of macroeconomic shocks, particularly inflation and the COVID-19 pandemic, in amplifying liquidity-induced instability. The proposed framework functions as an operational early warning system that enhances forecasting accuracy, model interpretability, and regulatory transparency, while repositioning FGAP as a forward-looking liquidity metric and offering both theoretical and practical contributions to financial risk management and supervisory practices in emerging economies.

Type of the article: Research Article

Abstract
One of the fundamental functions of commercial banks is providing credit to the public; however, with advancements in digital technology, this function is increasingly being performed by fintech lending companies as well. Accordingly, this study seeks to examine whether the growth of fintech credit in Indonesia acts as a substitute for or a complement to credit extended by commercial banks. The analysis utilizes monthly data from January 2018 to February 2023 and employs the Autoregressive Distributed Lag (ARDL) model to capture both short-run and long-run relationships between fintech lending and bank credit growth. The results indicate that the expansion of fintech credit exerts a positive and significant effect on the growth of bank lending, showing that fintech financing functions as a complement rather than a substitute. An increase in fintech credit is associated with an expansion of bank credit, implying that fintech lending enhances overall financial intermediation by reaching underserved segments and supporting credit distribution through formal banking channels. These findings suggest that fintech development does not crowd out bank lending but instead strengthens Indonesia’s credit ecosystem. The findings offer important guidance for regulators and other stakeholders in formulating suitable policies to respond to the rapid advancement of fintech services. With a balanced regulatory framework, effective oversight, constructive collaboration, and adequate digital infrastructure, Indonesia’s financial ecosystem has the potential for inclusive, efficient, and sustainable financial development.

Type of the article: Research Article

Abstract
This paper investigates the determinants of bank profitability in Oman. It covers two broad categories of traditional factors that determine bank profitability, namely bank-specific variables: capital adequacy, credit risk, liquidity risk, and operational efficiency; and macroeconomic variables: economic growth, inflation, industry concentration, credit growth, and interest rates. Due to the nature and small size of the Omani economy, the industry-specific factors are clubbed with macroeconomic factors. The findings show that the p-value (0.00) is well below the 5% significance level for both ROE and ROA proxies, leading to the acceptance of the null hypothesis of no co-integration. Moreover, Fisher’s chi-squared test statistics are 145.742 for ROE and 150.224 for ROA, strengthening the absence of a long-term relationship between both bank-specific and macroeconomic variables. Co-integration vectors with Fully Modified OLS show that CPI (Inflation) does not significantly influence ROE (p = 0.280), indicating that explanatory variables have no significant impact on ROE at 5% significance level. Similarly, in estimating ROA, neither CPI (p = 0.146) nor GDP (p = 0.435) reflects a significant effect, suggesting that these macroeconomic variables do not have a co-integrating impact on profitability metrics. The study indicates that bank profitability in Oman is sensitive to both internal and external factors. However, the degree to which each determinant affects a bank’s profitability in Oman varies from that observed in international studies. The findings have important implications for decision-makers in the banking sector when developing appropriate strategies, considering the sensitivity of each factor indicated in our study to bank profitability.

Acknowledgments
We express our gratitude to the management, staff, and students at the College of Banking and Financial Studies for their valuable support.

Type of the article: Research Article

Abstract
The article provides a comprehensive empirical assessment of the legal and operational regimes of digital asset circulation and their real impact on the financial market. To quantitatively measure the degree of state control, a composite Crypto Regulation Stringency Index (CRSI) was applied, constructed based on the OECD-JRC methodology. The index integrates 16 parameters across five fundamental areas (legal status, anti-money laundering, taxation, licensing, and consumer protection) for 61 countries (jurisdictions) as of 2025. The developed tool demonstrated high internal consistency and factor structure reliability (Cronbach’s α = 0.955).
To determine the market consequences of legal regulation, the index values were compared with the Chainalysis 2025 Global Crypto Adoption Index. The direct unconditional correlation between the stringency of rules and the scale of digital asset usage proved to be weak. However, a multivariate regression analysis conditional on a set of macroeconomic and institutional covariates (income level, digital infrastructure development, financial freedom, quality of the rule of law, and the specifics of the MiCA regulation) revealed a robust and statistically significant positive relationship. The reversal of the effect is consistent with a Simpson-type compositional effect: within groups of countries with comparable levels of economic development, clear and strict regulatory rules stimulate market activity. The findings extend the literature on comparative financial law and demonstrate that state control does not suppress the crypto-economy but rather serves as its stable institutional foundation.