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This chapter focuses on a case study of Kareem Exchange Company and its use of big data analysis to detect and prevent fraud and suspicious financial transactions. The chapter describes the various phases of the big data analysis cycle, including discovery, data preparation, model planning, model building, operationalization, and communicating results, and how the Kareem Exchange Company team implemented each phase. This chapter emphasizes the importance of identifying the business problem, understanding the resources and stakeholders involved, and developing an initial hypothesis to guide the analysis. The case study results demonstrate the potential of big data analysis to improve fraud detection capabilities in financial institutions, leading to informed decision making and action.

Financial technology (fintech) has emerged as a major player in the global financial system, providing a range of services such as payments, digital currencies, money transfers, loans, crowdsourcing, and insurance. Fintech startups in Arab countries have also gained traction due to economic openness and globalization. However, concerns remain about the safety, durability, and security of traditional financial services, especially with the increasing use of artificial intelligence (AI) and digitization. The Central Bank of Bahrain and other regulatory authorities need to balance risk avoidance with the global trend toward innovation in fintech, as well as ensure that these technologies are not used for fraud, money laundering, piracy, or terrorist financing. The Bahraini government and supervisory authorities must strike a balance between preserving the integrity and robustness of the financial and banking sector and developing innovation. This can be achieved by adjusting the rhythm of comparison, strengthening and enhancing the safety of banks, achieving financial stability, and ensuring compliance with laws and legislation. It is important to address gaps in regulatory rules, information security, and the business environment, and launch financial awareness at the community level before embracing the potential of fintech and its unseen future development at the level of cryptocurrencies and others. The current work examines the impact of Fintech on the Future of banking in Bahrain and the opportunities and challenges.

This study aims to see the moderating effect of board diversity on the relationship between ownership structure and real earnings management.

This study uses unbalanced panel data of 75 listed energy firms (346 firm-year observations) from three South Asian emerging economies (Bangladesh, India, and Pakistan) from 2015 to 2019. The two-step system GMM estimation is used for data analysis. This study also uses fixed effect regression to obtain robust findings.

The findings show that firms with a greater ownership concentration and managerial ownership significantly reduce real earnings management. In contrast, the data refute the idea that institutional and foreign ownership affect real earnings management. We also find that board diversity interacts significantly with ownership concentration and managerial ownership, meaning that board diversity moderates the negative link of the primary relationship that reduces real earnings management. On the other hand, board diversity has no interaction with institutional and foreign ownership, implying no moderating effect exists on the primary relationship.

To the best of the authors’ knowledge, this is unique research investigating how different ownership structures affect real earnings management in the emerging nations’ energy sector, which the earlier studies overlook. More specifically, this research focuses on how board diversity moderates the relationships between ownership structure and real earnings management, which could be helpful for future investors.

This paper aims to empirically investigate the moderating role of corporate governance (CG) in the capital structure-performance relationship.

The analysis is based on top Business Today-500 companies and covers a time span of 10 years. The fixed effect panel regression model is used to examine the impact of CG mechanisms on the relationship between capital structure and firm performance.

The core findings of the study indicate significant positive moderating role of board independence, board size and family ownership on the relationship between leverage and performance.

The results enable the managers of Indian firms to comprehend the significance of CG framework while taking financing decisions. The findings encourage managers to raise debt funds in those firms that adhere to good governance norms.

Unlike extant studies that emphasize on the moderating impact of single CG variable in leverage-performance relationship, the current work comprehensively examines the role of many CG factors that moderate the relationship between capital structure and firm performance. To the best of the authors’ knowledge, the present study is the first of its kind with respect to India.