A distinguished economist examines competition, regulation, and stability in today's global banks Does too much competition in banking hurt society? What policies can best protect and stabilize banking without stifling it? Institutional responses to such questions have evolved over time, from interventionist regulatory control after the Great Depression to the liberalization policies that started in the United States in the 1970s. The global financial crisis of 2007–2009, which originated from an oversupply of credit, once again raised questions about excessive banking competition and what should be done about it. Competition and Stability in Banking addresses the critical relationships between competition, regulation, and stability, and the implications of coordinating banking regulations with competition policies. Xavier Vives argues that while competition is not responsible for fragility in banking, there are trade-offs between competition and stability. Well-designed regulations would alleviate these trade-offs but not eliminate them, and the specificity of competition in banking should be accounted for. Vives argues that regulation and competition policy should be coordinated, with tighter prudential requirements in more competitive situations, but he also shows that supervisory and competition authorities should stand separate from each other, each pursuing its own objective. Vives reviews the theory and empirics of banking competition, drawing on up-to-date analysis that incorporates the characteristics of modern market-based banking, and he looks at regulation, competition policies, and crisis interventions in Europe and the United States, as well as in emerging economies. Focusing on why banking competition policies are necessary, Competition and Stability in Banking examines regulation's impact on the industry's efficiency and effectiveness.

This paper studies two new models in which banks face a non-trivial asset allocation decision. The first model (CVH) predicts a negative relationship between banks' risk of failure and concentration, indicating a trade-off between competition and stability. The second model (BDN) predicts a positive relationship, suggesting no such trade-off exists. Both models can predict a negative relationship between concentration and bank loan-to-asset ratios, and a nonmonotonic relationship between bank concentration and profitability. We explore these predictions empirically using a cross-sectional sample of about 2,500 U.S. banks in 2003 and a panel data set of about 2,600 banks in 134 nonindustrialized countries for 1993-2004. In both these samples, we find that banks' probability of failure is positively and significantly related to concentration, loan-to-asset ratios are negatively and significantly related to concentration, and bank profits are positively and significantly related to concentration. Thus, the risk predictions of the CVH model are rejected, those of the BDN model are not, there is no trade-off between bank competition and stability, and bank competition fosters the willingness of banks to lend.

This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1968.

We study a banking model in which banks invest in a riskless asset and compete in both deposit and risky loan markets. The model predicts that as competition increases, both loans and assets increase; however, the effect on the loans-to-assets ratio is ambiguous. Similarly, as competition increases, the probability of bank failure can either increase or decrease. We explore these predictions empirically using a cross-sectional sample of 2,500 U.S. banks in 2003, and a panel data set of about 2600 banks in 134 non-industrialized countries for the period 1993-2004. With both samples, we find that banks' probability of failure is negatively and significantly related to measures of competition, and that the loan-to-asset ratio is positively and significantly related to measures of competition. Furthermore, several loan loss measures commonly employed in the literature are negatively and significantly related to measures of bank competition. Thus, there is no evidence of a trade-off between bank competition and stability, and bank competition seems to foster banks' willingness to lend.

Introduction to Business covers the scope and sequence of most introductory business courses. The book provides detailed explanations in the context of core themes such as customer satisfaction, ethics, entrepreneurship, global business, and managing change. Introduction to Business includes hundreds of current business examples from a range of industries and geographic locations, which feature a variety of individuals. The outcome is a balanced approach to the theory and application of business concepts, with attention to the knowledge and skills necessary for student success in this course and beyond. This is an adaptation of Introduction to Business by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.

We use data for more than 2,600 European banks to test whether increased competition causes banks to hold higher capital ratios. Employing panel data techniques, and distinguishing between the competitive conduct of small and large banks, we show that banks tend to hold higher capital ratios when operating in a more competitive environment. This result holds when controlling for the degree of concentration in banking systems, inter-industry competition, characteristics of the wider financial system, and the regulatory and institutional environment.

We study versions of a general equilibrium banking model with moral hazard under either constant or increasing returns to scale of the intermediation technology used by banks to screen and/or monitor borrowers. If the intermediation technology exhibits increasing returns to scale, or it is relatively efficient, then perfect competition is optimal and supports the lowest feasible level of bank risk. Conversely, if the intermediation technology exhibits constant returns to scale, or is relatively inefficient, then imperfect competition and intermediate levels of bank risks are optimal. These results are empirically relevant and carry significant implications for financial policy.

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.