Search results

The primary objective of this study aims to intensively explore the environment of Indonesian regulations and laws related to the Islamic banking system and micro-, small- and medium-sized enterprises (MSME) and unveil the restrictive laws and regulatory flaws that potentially hinder the Islamic banking institution and MSME industry in achieving financial inclusion and promoting sustainable growth.

This paper implements a qualitative method by implementing a multi-case study research strategy, both from the Islamic banking institutions and the MSME industries. The data were gathered primarily through an interview approach by adopting purposive uncontrolled quota sampling.

The findings of this paper reveal two essential issues: First, the regulatory imbalances and restrictions could demotivate and hinder the efforts of Islamic banks in providing access to finance for the MSME segment, hence, encumbering the achievement of the financial inclusion agenda from the Islamic banking industry. Second, the flaws in MSME registration and taxation might discourage the formal MSMEs from extending their business license and prevent the informal MSME units from registering their business. This issue would potentially lower their chance of accessing external financing from the formal financial institutions and participating in supportive government programmes due to the absence of proper legality.

Since this paper only observed six Islamic banks and 22 MSME units in urban and rural locations in Indonesia using a case study approach, the empirical findings and case discussions were limited to those respective Islamic banks and MSME participants.

By referring to the recommendations as presented in this paper, two critical policy implications could be expected from adopting the proposed recommendations, among others: By addressing the issues of the regulatory imbalance associated with the Islamic banking industry and introduce the deregulatory policies on profit and loss sharing (PLS) scheme implementation, this approach will motivate the Islamic banking industry in serving the MSME sector better and provide greater access to financial services, particularly in using the PLS financing schemes. By resolving the problems on MSME registration and taxation, this strategy will enhance the sustainability of the formal MSMEs’ operation and encourage the informal ones to register, hence, improving their inclusion into the formal financing services and government assistance programmes.

The present study attempts to address the literature shortcomings and helps to fill the gaps – both theoretical and empirical – by incorporating the multi-case study among Indonesian Islamic banks and MSMEs to extensively explore the Indonesia regulatory environment pertaining to the Islamic banking system (supply-side) and MSMEs (demand-side), and thoroughly investigates and reveals the restrictive laws and regulatory flaws that could potentially hinder the Islamic banking institutions and MSME industries in attaining financial inclusion and contributing to sustainable development.

This study aims to explore the risk spillover effects among different sectors of the Chinese stock market after the outbreak of COVID-19 from both Internet sentiment and price fluctuations.

The authors develop four indicators used for risk contagion analysis, including Internet investors and news sentiments constructed by the FinBERT model, together with realized and jump volatilities yielded by high-frequency data. The authors also apply the time-varying parameter vector autoregressive (TVP-VAR) model-based and the tail-based connectedness framework to investigate the interdependence of tail risk during catastrophic events.

The empirical analysis provides meaningful results related to the COVID-19 pandemic, stock market conditions and tail behavior. The results show that after the outbreak of COVID-19, the connectivity between risk spillovers in China's stock market has grown, indicating the increased instability of the connected system and enhanced connectivity in the tail. The changes in network structure during COVID-19 pandemic are not only reflected by the increased spillover connectivity but also by the closer relationships between some industries. The authors also found that major public events could significantly impact total connectedness. In addition, spillovers and network structures vary with market conditions and tend to exhibit a highly connected network structure during extreme market status.

The results confirm the connectivity between sentiments and volatilities spillovers in China's stock market, especially in the tails. The conclusion further expands the practical application and theoretical framework of behavioral finance and also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management across stock sectors.

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.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

Considering the standards developed by the Sustainability Accounting Standards Board (SASB), this study aims to examine whether the link between material sustainability and financial performance depends on the extent to which the company is oriented toward stakeholders.

To test the predictions, 13,942 firm-year observations from 43 different countries are used, covering the period from 2010 to 2019. Using a hand-mapping approach to match the indicators suggested by the SASB with those of the ASSET4, the authors realize that there are 170 material sustainability indicators among 466 indicators of the ASSET4. The authors use three different methods to verify if the materiality matters, including the alphas obtained from the Fama and French factor models, comparing the average abnormal returns of the portfolios and the bootstrapped Cramer technique.

The findings show that companies investing in material sustainability activities perform better than those investing in immaterial activities. Also, consistent with the theoretical foundations, the authors find that the effect of investing in material sustainability activities is more pronounced in stakeholder-oriented countries than that in shareholder-oriented countries. The results are robust to a battery of sensitivity tests.

Owing to COVID-19 in late 2019, data from 2020 to 2022 have not been used to obtain reliable results.

The results obtained in the current research provide valuable guidance for investors to make investments considering the degree of materiality of sustainability activities in different industries. It also helps managers to increase the company’s financial performance, make efficient decisions related to investment in sustainability activities and find investment strategies on the material sustainability issues in their industries.

This study provides a clearer understanding of investment in sustainability activities in different industries by separating material and immaterial sustainability activities in stakeholder and shareholder-oriented countries, and the results obtained can change the perspective of investors and company managers regarding investing in such activities in different countries. Investing in more materiality sustainability activities than the immateriality dimension can be new opportunities for companies to achieve predetermined goals, help retain and attract business partners or be a source of innovation for new product lines or services. Internal morale and employee engagement may increase while increasing productivity and firm performance. This discussion opens the way for future research.

This study provides insight into the effect of investing in material and immaterial sustainability activities in different industries on the company’s performance in shareholder and stakeholder-oriented countries.

Integrating artificial intelligence (AI) into various industries, including the financial sector, has transformed them. This paper aims to examine the influence of integrating AI, including machine learning, process automation, predictive analytics and chatbots, on financial institutions and explores its various aspects and areas. The study aims to determine the impact of AI integration on financial services, products and customer experience.

The research study uses quantitative and qualitative methods, as well as secondary data analysis. It investigates four AI subfields: machine learning, process automation, predictive analytics and chatbots.

The research findings indicate that integrating AI, particularly in machine learning and chatbot subfields, holds promise and high strategic potential for financial institutions. These subfields can contribute significantly to enhancing financial services and customer experience. However, the significance of predictive analytics integration and process automation is relatively lower. Although these subfields retain their usefulness, they might necessitate alternative workflows and tools that incorporate human involvement. Overall, AI integration minimizes human interactions and errors in financial institutions.

The research study contributes original insights by exploring the specific subfields of AI within the financial industry and assessing their strategic significance. It provides recommendations for financial institutions to adopt AI integration partially in multiple phases, measure and evaluate the impact of the transformation and structure internal units and expertise to strategize adoption and change.

The banking industry faces increasing scrutiny from stakeholders regarding its environmental and social impacts, given its crucial role in fostering economic growth. Banks have been encouraged to adopt environmental, social and governance (ESG) practices to mitigate risks and safeguard their reputation. However, the effectiveness of ESG sensitivity within the banking industry is contingent upon ownership and structural factors. The extent to which banks can integrate ESG considerations into their operations and decision-making processes may vary based on their ownership structures. Therefore, this study aims to examine if the impact of ESG on the performance of Indian banks varies between private and public sector banks.

The study employs six years of panel data from two separate samples of 12 private sector banks and 10 public sector banks in India. It utilises fixed and random effect estimation techniques with robust standard errors to derive accurate and reliable econometric results.

The main findings of this study reveal intriguing insights into the relationship between ESG factors and bank performance, considering the influence of ownership structure. For private sector banks, the ESG composite score, particularly the social dimension, negatively impacts financial performance. However, there is a contrasting positive effect on efficiency. In contrast, public sector banks demonstrate a positive and significant association between the environmental score and return on equity and non-performing assets.

The findings highlight the need for tailored strategies that align with ownership structure to achieve sustainable financial and societal outcomes in the banking industry. Furthermore, it emphasises the need for private-sector banks to streamline their ESG initiatives, especially in the social dimension, to mitigate negative impacts on their financial performance.

This study introduces a novel dimension by addressing the “one size fits all” bias in prior research that overlooked bank ownership differences when examining the impact of ESG factors on bank performance.

This study aims to examine the impact of intellectual capital (IC) on default risk in Indian companies listed on the National Stock Exchange.

This study applies panel data regression analysis to derive a relationship between IC and default risk for the sample period 2013–2022. The value-added intellectual coefficient (VAIC) of Pulic (2000) has been applied to measure IC performance, and default risk is estimated using the revised Z-score model of Altman (2000).

The results revealed a positive association between Z-score and VAIC. It implies that a higher value of VAIC improves financial stability and leads to a lower likelihood of default. The findings further suggest that new default forecasting models can be experimented with IC indicators for better default prediction.

The findings can have implications for investors and banks. This paper provides evidence of IC performance in improving the financial solvency of firms. Investors and financial institutions should invest their resources in a healthy firm that effectively manages and invests in their IC. It will eventually award investors and creditors high returns through efficient value-creation processes.

This study provides evidence of IC performance in improving the financial solvency of Indian high-defaulting firms, which lacks sufficient evidence in this domain of research. Numerous studies exist examining the relationship between firm performance and IC value, but this area is inadequately focused and underresearched. This study, therefore, fills the research gap from an Indian perspective.

Sustainability is essential to the ongoing operations of banks, though it is much less clear how Islamic corporate governance (ICG) promotes economic sustainability (ES) and thereby prevents bankruptcy. To explore the unexplored, this study aims to examine the efficacy of ICG in preventing bankruptcy and enhancing the ES of Islamic banks operating in Pakistan.

The current study measures ES through Altman's Z-score to analyze the level of the industry's stability and consequently examines the effect of ICG on the ES of Islamic banks in Pakistan for the post-financial-crises period. Using the country-level data, this study utilized a fixed-effect model and two-stage least squares (2SLS) techniques on balanced panel data spanning from 2009 to 2020 to provide empirical evidence.

The empirical results unveiled that board size and meetings have a significant positive influence on the ES while managerial ownership demonstrated an unfavorable effect on ES. Interestingly, the insignificant effect of women directors became significant with the inclusion of controlled variables. Overall, the findings indicate that ICG is an efficient tool for promoting ES in Islamic banks and preventing them from the negative effects of emerging crises.

The findings provide concrete insights for policymakers, regulators and other concerned stakeholders to execute a sturdy corporate governance system that not only oversees the economic, social and ethical aspects but also provides measures to alleviate the impacts of potential risks like the COVID-19 pandemic.

Examining the role of ICG in alleviating bankruptcy risk is an informative and useful endeavor for all social actors.

To the best of the authors’ knowledge, this study is one of the first efforts to provide evidence-based insights on the role of ICG in preventing bankruptcy and offers a potential research direction for ES.

In the evolving landscape of global remittances, this study systematically explores cryptocurrency's transformative impact on remittance services through a comprehensive literature review and bibliometric analysis.

Through meticulous PRISMA-guided analysis, the research identifies cryptocurrency technology as a pivotal force in enhancing remittance efficiency, reducing costs and broadening access contributing significantly to financial inclusion.

Findings revealed that cryptocurrency technology could significantly enhance remittance services, offering improved efficiency, reduced costs and increased accessibility. This suggests a transformative potential for financial inclusion, presenting a compelling case for broader adoption and regulatory support to leverage these benefits effectively.

By integrating recent research, this work underlines the urgent need for broader adoption and regulatory support to leverage these benefits effectively. It offers novel insights for institutions and policymakers, highlighting the potential for technology adoption in remittances to enhance financial inclusivity.

More cryptocurrency studies are needed to concentrate on remittance markets. Thus, this investigation constitutes a unique addition to the field. Additional investigation in this domain presents significant possibilities for future exploration and progress.