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This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).

Academic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.

Using data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.

Our analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.

Our results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

Purpose: The study aimed to investigate the impact of corporate governance (CG), non-performing loans (NPLs), and bank size (BS) on the financial performance (FP) of banking institutions in Kosovo.

Need for the study: Despite the growth and development of the banking sector in Kosovo, there’s a dearth of comprehensive research examining the key factors influencing their FP. This study aimed to bridge this gap, with a focus on CG, NPLs, and BS.

Methodology: The research employed a multiple regression model to analyse a sample of banking institutions in Kosovo over the period 2006–2021. The key variables included various CG factors, the level of NPLs, and BS, with FP measured through return on assets (ROA) and return on equity (ROE).

Findings: The study found a significant positive relationship between CG factors and bank performance (BP), particularly board size and board independence. Conversely, a significant negative relationship was observed between the level of NPLs and BP. Furthermore, the study revealed a non-linear relationship between BS and FP, with economies of scale contributing to improved performance up to a certain threshold, after which further increases in size led to inefficiencies and lower performance.

Practical implications: The findings of this study carry important implications for policymakers, banking practitioners, and academics. It underlines the importance of sound CG, effective risk management, and maintaining an optimal BS to enhance the FP of banks in Kosovo. It is suggested that these factors should be considered in the formulation of future banking regulations and strategies.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

The purpose of this paper is to scrutinise the effectiveness of four derivative exchanges’ enforcement efforts since 2007. These exchanges include the Commodity Exchange Inc. and ICE Futures US from the United States and ICE Futures Europe and the London Metal Exchange from the UK.

The paper examines 799 enforcement notices published by four exchanges through a behavioural science lens: HUMANS conceived by Hunt (2023) in Humanizing Rules: Bringing Behavioural Science to Ethics and Compliance.

The paper finds the effectiveness of the exchanges’ enforcement efforts to be a mixed picture as financial markets transition from the digital to artificial intelligence era. Humans remain a key cog in the wheel of market participants’ trading operations, albeit their roles have changed. Despite this, some elements of exchanges’ enforcement regimes have not kept pace with the move from floor to remote trading. However, in other respects, their efforts are or should be, effective, at least in behavioural terms.

The paper’s findings are arguably limited to exchanges based in Anglophone jurisdictions. The information published by the exchanges is variable, making “like-for-like” comparisons difficult in some areas.

The paper makes several recommendations that, if adopted, could help exchanges to increase the potency of their enforcement programmes.

A key aim of the paper is to shift the lens through which the debate concerning the efficacy of exchange-level oversight is conducted. Hitherto, a legal lens has been used, whereas this paper uses a behavioural lens.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

Free banking theory, as developed in Adam Smith’s 1776 treatise, “The Wealth of Nations” is a useful tool in determining the extent to which the “invisible hand of the market” should prevail in regulatory policy. The purpose of this study is to provide a timely review of the literature, evaluating the theory’s relevance to regulation of financial technology generally and cryptocurrencies (cryptos) specifically.

The methodology is qualitative, applying free banking theory as developed in the literature to technology-defined environments. Recent legislative developments in the regulation of cryptocurrencies in the UK, European Union and the USA, are drawn upon.

Participants in volatile cryptocurrency markets should bear the consequences of inadvisable investments in accordance with free banking theory. The decentralised nature of cryptocurrencies and the exchanges on which these are traded militate against coordinated oversight by central banks, supporting a qualified free banking approach. Differences regarding statutory definitions of cryptos as units of exchange, tokens or investment securities and the propensity of these to transition between categories across the business cycle render attempts at concerted classification at the international level problematic. Prevention of criminality through extension of Suspicious Activity Reporting to exchanges and intermediaries should be the principal objective of policymakers, rather than definitions of evolving products that risk stifling technological innovation.

The study proposes that instead of a traditional regulatory approach to cryptos, which emphasises holders’ safety and compensation, a free banking approach combined with a focus on criminality would be a more effective and pragmatic way forward.

The purpose of this paper is to examine whether board characteristics moderate the relationship between capital adequacy regulation and bank risk-taking of universal banks in Sub-Saharan Africa (SSA).

The paper uses 700 bank-year observations of universal banks in SSA between 2009 and 2019. The paper further uses the two-step generalized method of moments as the baseline estimator.

The paper finds that capital adequacy regulation is positively related to overall bank and liquidity risks. Nonetheless, capital adequacy regulation increases credit risk in the sampled banks. The paper further reports that board characteristics individually and significantly moderate the relationship between capital adequacy regulation and risk-taking.

The findings have implications for regulators of universal banks that board characteristics matter for capital adequacy regulation to impact risk-taking behavior.

The paper extends the existing literature on the effect of board characteristics on the capital adequacy regulations and risk-taking behavior nexus of universal banks.