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The increased capital requirements and the implementation of new liquidity standards under Basel III sparked various concerns among researchers, academics and other stakeholders. The question is whether Basel III regulation is ideal, that is, adequate to deal with a crisis, such as the 2007–2009 global financial crisis? The purpose of this paper is threefold: First, perform a stress testing exercise on the US banking sector, while examining liquidity and solvency risk indicators jointly under the Basel III regulatory framework. Second, allow the study to cover the post-crisis period, while referring to key Basel III regulatory requirements. And third, focus on the resilience of domestic systemically important banks (D-SIBs), which are supposed to support the US financial system in times of stress and therefore whose failure causes the entire financial system to fail.

The authors used a sample of the 24 largest US banks observed over the period Q1-2015 to Q1-2021 and a scenario-based vector autoregressive conditional forecasting approach.

The authors found that the model successfully produces accurate forecasts and simulates the responses of the solvency and liquidity indicators to different real and historical macroeconomic shocks. The authors also found that the US banking sector is resilient and can withstand both historical and hypothetical macroeconomic shocks because of its compliance with the Basel III capital and liquidity regulations, which consist of encouraging banks to hold high-quality liquid assets and stable funding resources and to strengthen their capital, which absorbs the losses incurred in a crisis.

The authors developed a framework for testing the resilience of the US banking sector under macroeconomic shocks, while examining liquidity and solvency risk indicators jointly under Basel III regulatory framework, a point not yet well studied elsewhere, and most studies on this subject are based on precrisis data. The authors also focused on the resilience of D-SIBs, whose failure causes the failure of the entire financial system, which previous studies have failed to examine.

The purpose of this study is to analyse cyberfraud in the South African banking industry using a multiple regression approach and develop a predictive model for the estimation and prediction of financial losses due to cyberfraud.

To mitigate the occurrence of cyberfraud, this study uses the multiple regression approach to correlate the relationship between financial loss and cyberfraud activities. The cyberfraud activities in South Africa are classified into three, namely, digital banking application, online and mobile banking fraud. Secondary data that captures the rate of cyberfraud occurrences within these three major categories with their resulting financial losses were used for the multiple regression analysis that was carried out in the Statistical Package for Social Science (SPSS, 2022 environment).

The results obtained indicate that the South African financial institutions still incur significant financial losses due to cyberfraud perpetration. The two main independent variables used to estimate the magnitude of financial loss in the South Africa’s banking industry are online (internet) banking fraud (X2) and mobile banking fraud (X3). Furthermore, a multiple regression model equation was developed for the prediction of financial loss as a function of the two independent variables (X2 and X3).

This study adds to the literature on cyberfraud mitigation. The findings may promote the combat against cyberfraud in the South Africa’s financial institutions. It may also assist South Africa’s financial institutions to predict the financial loss that financial institutions can incur over time. It is recommended that South Africa’s financial institutions pay attention to these two key variables and mitigate any associated risks as they are crucial in determining their profitability.

Existing literature indicated significant financial losses to cyberfraud perpetration without establishing any relationship between the magnitude of losses incurred and the prevalent forms of cyberfraud. Thus, the novelty of this study lies in the analysis of cyberfraud in the South African banking industry using a multiple regression approach to link financial losses to the perpetration of the prevalent forms of cyberfraud. It also develops a predictive model for the estimation and projection of financial losses.

The study examines whether the Basel-III regulations impact the financial performance, operational efficiency and resilience of Indian banks. Further, the study tests whether there is a variance in the impact between private- and public-sector banks.

The study uses panel data regression on data from 16 private- and 12 public-sector banks from the years 2016–2022. Random-effect estimation is used, and robust standard errors are calculated.

The main findings indicate that the Basel-III regulations related to capital and leverage boost public-sector banks' financial performance and resilience. However, a similar impact is not detected in the case of private-sector banks.

The findings signify that the Basel-III framework does not address the differences between public and private-sector banks. Therefore, the policy implications are of practical importance and indicate that Basel-III regulations should not be considered a one-size-fits-all type of bank. Instead, policymakers should consider the structural differences between private and public-sector banks concerning Basel-III regulations.

The study addresses a significant limitation of the Basel-III regulations, which, in their current state, somehow fail to account for the differences between the public- and private-sector banks.

This study aims to determine how Basel III capital requirements affect the stability of Islamic banks globally during the global financial crisis and the COVID-19 pandemic.

The secondary data for all Islamic banks worldwide from 2004 to 2021 is obtained from the FitchConnect database. The main technique was a two-step generalized method of moment (GMM) system, and the data were tested using pooled ordinary least squares, fixed effects and difference GMM models for robustness checks.

Regression results support the moral hazard hypothesis based on evidence that both the total capital ratio and the Tier 1 capital ratio have a statistically significant positive impact on the stability of Islamic banks globally. Furthermore, neither the global financial crisis of 2008–2009 nor COVID-19 (2020–2021) significantly impacted the stability of Islamic banks worldwide. The results are robust across alternative measures of stability, capital buffers, dummy variables and estimation techniques. According to the descriptive statistics, the number of Islamic banks that disclose their regulatory capital ratios to the public has increased over the study period, and the mean of total capital and Tier 1 ratios are considerably greater than what is required by Basel II and Basel III.

Bankers, regulators and policymakers should benefit from the evidence on capital and risk management in Islamic banking according to Basel Committee on Banking Supervision (BCBS) and Islamic financial services board (IFSB) international standards in various jurisdictions.

This research builds on earlier studies that were both beneficial and instructive by exploring the relationship between BCBS and IFSB capital guidelines and the trustworthiness of Islamic banks in greater depth. This study uses numerous capital ratios, buffers and stability measures to provide an international context for research on Islamic banking. In addition, the database is up-to-date to include information about the COVID-19 pandemic aftereffects in the year 2021. This study also introduces the Basel membership of Islamic banks to provide context for countries still at the Basel II stage or are yet to begin implementing the Basel III international standard.

This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.

This research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).

The main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.

Since the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.

The results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.

Previous studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.

Managing project completion within the stipulated time is significant to all firms' sustainability. Especially for software start-up firms, it is of utmost importance. For any schedule variation, these firms must spend 25 to 40 percent of the development cost reworking quality defects. Significantly, the existing literature does not support defect rework opportunities under quality aspects among Indian IT start-ups. The present study aims to fill this niche by proposing a unique mathematical model of the defect rework aligned with the Six Sigma quality approach.

An optimization model was formulated, comprising the two objectives: rework “time” and rework “cost.” A case study was developed in relevance, and for the model solution, we used MATLAB and an elitist, Nondominated Sorting Genetic Algorithm (NSGA-II).

The output of the proposed approach reduced the “time” by 31 percent at a minimum “cost”. The derived “Pareto Optimal” front can be used to estimate the “cost” for a pre-determined rework “time” and vice versa, thus adding value to the existing literature.

This work has deployed a decision tree for defect prediction, but it is often criticized for overfitting. This is one of the limitations of this paper. Apart from this, comparing the predicted defect count with other prediction models hasn’t been attempted. NSGA-II has been applied to solve the optimization problem; however, the optimal results obtained have yet to be compared with other algorithms. Further study is envisaged.

The Pareto front provides an effective visual aid for managers to compare multiple strategies to decide the best possible rework “cost” and “time” for their projects. It is beneficial for cost-sensitive start-ups to estimate the rework “cost” and “time” to negotiate with their customers effectively.

This paper proposes a novel quality management framework under the Six Sigma approach, which integrates optimization of critical metrics. As part of this study, a unique mathematical model of the software defect rework process was developed (combined with the proposed framework) to obtain the optimal solution for the perennial problem of schedule slippage in the rework process of software development.

Agricultural banks likely respond differently to economic downturns compared to nonagricultural banks. Limited previous research has examined the performance of agricultural banks under economic crisis and in the presence of banking regulations. This study aims to explore agricultural banks' responses to economic and regulation shocks relative to nonagricultural banks.

This study uses bank-quarter level data from 2002 to 2022 for virtually all commercial banks in the U.S. In this research, the Z-score measures the bank’s default risk, the return on assets measures bank profitability and changes in amount of farm loans indicate the wider impact on the agricultural sector. Effects of the financial crisis, Basel III reforms to banking regulation and the coronavirus (COVID-19) pandemic on these banking measures are assessed using distinct empirical frameworks. The empirical estimations use various subsamples based on bank types, bank sizes and time periods.

Economic downturns are associated with fluctuations in returns and the risk of default of commercial banks. Agricultural banks appeared to be more resilient to economic downturns than nonagricultural banks. However, Basel III regulated agricultural banks were more likely to fail amidst the pandemic-related economic shocks than the regulated non-agricultural banks.

This study examines the resiliency of agricultural banks during economic downturns and under postfinancial crisis regulation. This is one of the first empirical works to analyze the effectiveness of Basel III regulation across bank types and sizes considering the COVID-19 pandemic. The key finding suggests that banking regulation should consider not only size heterogeneity but also the heterogeneity in lending portfolios.

This study aims to examine the triple relationship between capital regulation, banking lending and economic growth in a dual markets. Specifically, the author seeks to explore how changes in capital regulation can impact banking lending practices and subsequently influence economic growth, while also investigating the reciprocal effects of banking lending on economic growth.

The author follows several previous studies such as Shrieves and Dahl (1992), Beck and Levine (2002), Altunbas et al. (2007), Saeed et al. (2020) and Stewart et al. (2021) to identify a system of three equations, regarding economic growth, capital and banking financing growth, respectively. The author estimates the parameters of all equations simultaneously using the seemingly unrelated regression method (Zellner, 1962) for a sample of 46 Islamic banks and 113 conventional banks during 2002–2022. These banks operate in 13 Muslim countries from Middle East and North Africa and Southeast Asia.

The author’s findings demonstrate that in the case of Islamic banking, an increase in loan growth stimulates economic growth, while an increasing capital ratio positively influences economic growth but is accompanied by a reduction in loan growth. This result corroborates the findings of Stewart et al. (2021), which indicate that regulatory capital reduces unstable credit while improving gross domestic product growth. However, in the case of conventional banks, the response to an increase in loan growth on Gross Domestic Product Per Capita Growth (GDPCG) is ambiguous, while the capital ratio improves GDPCG and promotes LOANG, which, in turn, increases risk.

The Islamic banks can continue to significantly contribute to economic growth by effectively directing their available capital toward viable investment opportunities and supporting sustainable financial practices, even in the presence of potential constraints on loan growth. As for conventional banks, they are invited to increase their capital levels to ensure a strong and resilient financial system that can support lending and facilitate economic growth.

To the best of the author’s knowledge, this paper is the first to explore the triple relationship between capital requirements, Islamic bank lending and economic growth.

Financial crime presents a serious threat to the stability and integrity of the global financial system. To combat illicit financial activities, regulatory bodies worldwide have implemented various measures, including the requirement for financial institutions to assess the financial crime risks they are exposed to in the jurisdictions they operate in. These risks include inadequate anti-money laundering and countering the financing of terrorism frameworks and other financial crime risks that have significant strategic implications for firms’ geographical footprints and customer risk classifications. This paper aims to make a contribution to the literature by undertaking a cross-country analysis of 158 countries to shed light on what drives perceived jurisdiction risk of the UK financial services firms.

Capturing firms’ perceptions of financial crime risk requires significant data collection efforts, including surveys and interviews with key personnel. This can be highly resource-intensive and may require access to sensitive information that firms may be reluctant to share. Furthermore, the dynamic nature of financial crime risks means that perceptions can change rapidly in response to changes in the regulatory and geopolitical landscape. As a result, capturing and monitoring firms’ perceptions of financial crime risks requires ongoing monitoring and analysis. Capturing firms’ perceptions of financial crime risks at a cross-jurisdictional level is a particularly complex and challenging task that requires careful consideration of a range of factors. As a result of data limitations, empirical investigation of the factors underlying the firms’ perceptions of jurisdiction risk is in its infancy. This paper uses regulatory financial crime data from the UK in a multivariate regression analysis, following a general-to-specific approach where any redundant variables were removed from the general model sequentially.

Results suggest that perceived jurisdiction risk is significantly and positively associated with evasion of tax and regulations, while it is significantly and negatively associated with political stability and regulatory stringency. These have important implications for home and host supervisors with respect to the factors that drive perceived jurisdiction risks and the evaluation of the nature of inherent financial crime risks within regulated firms. The findings confirm the critical role of the shadow economy, political stability and regulatory rigor in shaping jurisdiction risk perceptions. From a policy standpoint, the findings support the case for taking prompt policy action to identify, prioritize and implement specific and targeted measures with respect to the shadow economy, political stability and rigor of regulations to improve international firms’ perceptions of jurisdiction risk.

While there exists different measures of financial crime risk, it is notoriously challenging to capture firms’ perceptions of it, particularly at a cross-jurisdiction level. This is because financial crime risks can vary significantly across different jurisdictions due to differences in legal and regulatory frameworks, cultural norms and levels of economic development. This makes it difficult for firms to compare and evaluate the financial crime risks they face in different jurisdictions. Besides, firms’ perceptions of financial crime risks can be influenced by a range of subjective factors, including personal experiences, media coverage and hearsay. These perceptions may not always align with objective risk assessments, which are based on more systematic and empirical methods of risk measurement. This paper contributes to the existing literature by undertaking a cross-country analysis drawing on a unique set of UK regulatory financial crime data, which is based on a total of 1,900 annual financial crime data regulatory return (REP-CRIM) submissions to the UK’s Financial Conduct Authority.

In 2018, the International Financial Reporting Standard 9-Financial Instruments became mandatory, effectively changing the underlying accounting principles of financial instruments. This paper systematically reviews the academic literature on the implementation effects of IFRS 9, providing a coherent picture of the state of the empirical literature on IFRS 9.

The study thrives on a systematic review approach by analyzing existing academic studies along the following three broad categories: adoption and implementation, impact on financial reporting, and risk management and provisioning. The study concludes by providing research prospects to fill the identified gaps.

We document data-related issues, forecasting uncertainties and the interaction of IFRS 9 with other regulatory standards as implementation challenges encountered. Also, we observe cross-country heterogeneity in reporting quality. Furthermore, contrary to pre-implementation expectations, we find improvement in risk management. This suggests that despite the complexities of the new regulatory standard on financial instruments, it appears to be more successful in achieving the intended objective of enhancing better market discipline and transparency rather than being a regulatory overreach.

As the literature on IFRS 9 is burgeoning, we provide state-of-the-art guidance and direction for researchers with a keen interest in the economic significance and implications of IFRS 9 adoption. The study identifies gaps in the literature that require further research, specifically, IFRS 9 adoption and firm’s hedging activities, IFRS 9 implications on non-financial firms. Lastly, existing studies are mostly focused on Europe and underscore the need for more research in under-researched jurisdictions, particularly in Asia and Africa. Also, to standard setters, policymakers and practitioners, we provide some insight to aid the formulation and application of standards.