Template-Type: ReDIF-Article 1.0 Author-Name: Alper Kara Author-X-Name-First: Alper Author-X-Name-Last: Kara Author-Name: Jiafan Li Author-X-Name-First: Jiafan Author-X-Name-Last: Li Title: Gender, ethnicity and SMEs' access to finance: a systematic literature review of global empirical evidence Abstract: We systematically survey the global empirical evidence on gender and ethnicity implications of small and medium enterprises' (SMEs) access to finance in the last two decades. We find overwhelming evidence that women-owned SMEs encounter greater financial constraints, and seek less financing, in comparison to men-owned SMEs. Borrowing discouragement and fear of being rejected by creditors are identified as leading causes of women's non-participation in external borrowing. We find scarce evidence of systematic gender-based discrimination by lenders. However, there is evidence that women face higher interest and rejection rates and stringent lending criteria compared to men. We find that ethnic-minority-owned SMEs experience greater financial constraints. In the USA, evidence of ethnicity-based-discrimination is found; however, it is not common across the world. Our findings also show that ethnic-minority-owned SMEs demand for and ability to obtain external finance decreases further during and after economic crisis periods. We provide avenues for further research. Journal: Int. J. of Banking, Accounting and Finance Pages: 181-212 Issue: 1/2 Volume: 15 Year: 2025 Keywords: small and medium enterprises; SMEs; gender; women; ethnicity; minority; access to credit; systematic review; financial inclusion; financial exclusion. File-URL: http://www.inderscience.com/link.php?id=146519 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injbaf:v:15:y:2025:i:1/2:p:181-212 Template-Type: ReDIF-Article 1.0 Author-Name: Santiago Carbó-Valverde Author-X-Name-First: Santiago Author-X-Name-Last: Carbó-Valverde Author-Name: Francisco Rodríguez-Fernández Author-X-Name-First: Francisco Author-X-Name-Last: Rodríguez-Fernández Title: Banking in the era of artificial intelligence: a survey of the economic, social and strategic implications Abstract: Integrating artificial intelligence (AI) into banking platforms represents a transformative shift in the financial services industry, driven by the need for enhanced efficiency, improved customer experience, and robust security measures. This article analyses the economic, social, and strategic implications of AI adoption in banking. Through a comprehensive literature review, the study examines the impact of AI on operational efficiency, customer experience, security, and financial inclusion. It also addresses the ethical and regulatory challenges associated with AI, including algorithmic bias, transparency, and compliance. The findings underscore the importance of developing ethical guidelines and regulatory frameworks to ensure the responsible use of AI in banking. Strategic recommendations for banks include investing in AI talent, fostering collaborations, adopting a customer-centric approach, and ensuring ethical AI deployment. Future research directions are also suggested to explore further the potential of AI in enhancing banking services and promoting financial inclusion. Journal: Int. J. of Banking, Accounting and Finance Pages: 164-180 Issue: 1/2 Volume: 15 Year: 2025 Keywords: artificial intelligence; banking; digital transformation; financial inclusion; operational efficiency; regulatory compliance; ethical considerations. File-URL: http://www.inderscience.com/link.php?id=146534 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injbaf:v:15:y:2025:i:1/2:p:164-180 Template-Type: ReDIF-Article 1.0 Author-Name: Fatima Cardias Williams Author-X-Name-First: Fatima Cardias Author-X-Name-Last: Williams Author-Name: Jonathan Williams Author-X-Name-First: Jonathan Author-X-Name-Last: Williams Title: Does size matter? Pay gaps, non-CEO executives, and bank stability Abstract: We examine the effect of pay gaps between CEOs and non-CEO executives on bank stability for a sample of large, mostly international banks. Our primary result is that larger pay gaps are associated with an increase in bank stability and a decrease in portfolio risk and leverage risk. This result is robust to mandated changes in compensation arrangements and differences in national cultures. We find that the effect of pay gaps on stability and risk is sensitive to the power of bank CEOs. It suggests that powerful CEOs and senior non-CEOs exhibit a level of conservatism which both counters the effect of tournament incentives for junior non-CEOs to take risks and protects the pay and status of senior executives. Journal: Int. J. of Banking, Accounting and Finance Pages: 44-83 Issue: 1/2 Volume: 15 Year: 2025 Keywords: banks; compensation; pay gap; tournaments; bank stability; executive directors. File-URL: http://www.inderscience.com/link.php?id=146542 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injbaf:v:15:y:2025:i:1/2:p:44-83 Template-Type: ReDIF-Article 1.0 Author-Name: Iftekhar Hasan Author-X-Name-First: Iftekhar Author-X-Name-Last: Hasan Author-Name: Tahseen Hasan Author-X-Name-First: Tahseen Author-X-Name-Last: Hasan Author-Name: Kose John Author-X-Name-First: Kose Author-X-Name-Last: John Title: Tax authority attention and financial reporting Abstract: We study the effects of tax authority (IRS) attention on a firm's financial reporting. We explore whether firms institute a higher degree of accounting conservatism in response to IRS monitoring. Using data on IRS acquisition of public firms' 10-K financial disclosures to proxy for IRS attention, we find that when firms are under IRS attention, they tend to initiate higher levels of unconditional and, to some extent, conditional accounting conservatism. We alleviate some of the endogeneity concerns by using pre- and post-IRS attention environments between the treated group (firms with IRS attention) and a propensity score that matches the control group of firms (no IRS attention). These results withstand several robustness tests and subsample analyses. Journal: Int. J. of Banking, Accounting and Finance Pages: 84-119 Issue: 1/2 Volume: 15 Year: 2025 Keywords: IRS attention; tax; tax monitoring; tax enforcement; accounting conservatism; financial disclosure; financial reporting. File-URL: http://www.inderscience.com/link.php?id=146543 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injbaf:v:15:y:2025:i:1/2:p:84-119 Template-Type: ReDIF-Article 1.0 Author-Name: Dimitris K. Chronopoulos Author-X-Name-First: Dimitris K. Author-X-Name-Last: Chronopoulos Author-Name: John O.S. Wilson Author-X-Name-First: John O.S. Author-X-Name-Last: Wilson Author-Name: Muhammed H. Yilmaz Author-X-Name-First: Muhammed H. Author-X-Name-Last: Yilmaz Title: State ownership and bank lending: evidence from Turkish banking Abstract: We investigate state bank lending behaviour during crisis periods by exploiting the global financial crisis as an exogenous shock, and a high-frequency spatial banking dataset. Using Turkey for the period 2007Q4-2011Q4 as a setting, our results suggest that state banks maintain lending relative to domestic private and foreign banks. Moreover, state banks appear to play a mitigating role in alleviating market failures rather than engaging in politically motivated lending. Overall, our results highlight the importance of state bank lending during periods of financial turmoil. Journal: Int. J. of Banking, Accounting and Finance Pages: 5-43 Issue: 1/2 Volume: 15 Year: 2025 Keywords: state banks; market failures; difference-in-differences; DiD; political motives. File-URL: http://www.inderscience.com/link.php?id=146545 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injbaf:v:15:y:2025:i:1/2:p:5-43 Template-Type: ReDIF-Article 1.0 Author-Name: Barbara Casu Author-X-Name-First: Barbara Author-X-Name-Last: Casu Author-Name: Claudia Girardone Author-X-Name-First: Claudia Author-X-Name-Last: Girardone Title: From deregulation to the twin transition: exploring banking strategies for sustainability and digitalisation Abstract: This article explores the evolution of empirical banking research in developed countries over the past 30 years, reflecting the sector's adaptation to changing regulatory and economic environments. We identify key areas that have shaped banking research, including priorities and strategies during the deregulation era and the culture crisis triggered by the Global Financial Crisis. The discussion then shifts to two critical emerging themes: sustainability and digitalisation, highlighting their convergence in a 'twin transition' that addresses the interconnected challenges of climate change and technological disruption, both of which demand transformative approaches to banking practices, strategies, and policies. Journal: Int. J. of Banking, Accounting and Finance Pages: 139-163 Issue: 1/2 Volume: 15 Year: 2025 Keywords: banking sector deregulation; great financial and culture crisis; net zero; sustainable digitalisation; twin transition. File-URL: http://www.inderscience.com/link.php?id=146546 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injbaf:v:15:y:2025:i:1/2:p:139-163 Template-Type: ReDIF-Article 1.0 Author-Name: David P. Newton Author-X-Name-First: David P. Author-X-Name-Last: Newton Author-Name: Steven Ongena Author-X-Name-First: Steven Author-X-Name-Last: Ongena Author-Name: Ru Xie Author-X-Name-First: Ru Author-X-Name-Last: Xie Author-Name: Binru Zhao Author-X-Name-First: Binru Author-X-Name-Last: Zhao Title: Leveraged loans: is high leverage risk priced in? Abstract: We investigate the impact of the 2014 Interagency Clarification on the leverage risk premium for bank- and non-bank-originated loans. Using a novel dataset from 2011 to 2019, we show that leveraged loan spreads have declined rapidly for non-bank facilities relative to bank facilities since the introduction of the 2014 Interagency Clarification. The decline in leveraged loan spreads is significant for highly leveraged borrowers, especially when term loans are involved. We further demonstrate that a higher degree of information asymmetry, driven by an increase in covenant-lite loan issuance and weaker investor protection, is strongly associated with a narrower leverage risk premium. Journal: Int. J. of Banking, Accounting and Finance Pages: 120-138 Issue: 1/2 Volume: 15 Year: 2025 Keywords: leverage risk; syndicated loan pricing; leveraged loan; information asymmetry. File-URL: http://www.inderscience.com/link.php?id=146550 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injbaf:v:15:y:2025:i:1/2:p:120-138 Template-Type: ReDIF-Article 1.0 Author-Name: Asif M. Huq Author-X-Name-First: Asif M. Author-X-Name-Last: Huq Author-Name: Wonder Mahembe Author-X-Name-First: Wonder Author-X-Name-Last: Mahembe Title: Influence of sampling methods on bankruptcy prediction: normal vs. abnormal economic conditions Abstract: Bankruptcy prediction research has largely emphasised model performance through feature selection and algorithm optimisation, while the equally important challenge of class imbalance remains underexplored. Most studies also focus on publicly listed firms, reflecting the accessibility of standardised data. Our study makes a novel and valuable contribution by leveraging a large-scale dataset of private firms - an economically significant yet understudied segment. Using 2,039,222 firm-year observations from 430,800 private firms between 2012 and 2021, we evaluate four machine learning models, five sampling techniques, and two distinct economic periods. Results show that sampling choice strongly influences accuracy and feature relevance, depending on macroeconomic conditions. Importantly, simple interpretable models built on theoretically grounded features (e.g., Altman, 1968) achieve robust predictions, challenging prevailing reliance on complex methods, while Extreme Gradient Boosting (XGBoost) consistently outperforms alternatives. By focusing on private firms, the study provides unique insights and underscores methodological choices crucial for reliable bankruptcy prediction. Journal: Int. J. of Banking, Accounting and Finance Pages: 1-32 Issue: 5 Volume: 15 Year: 2025 Keywords: bankruptcy prediction; data imbalance; machine learning; sampling methods. File-URL: http://www.inderscience.com/link.php?id=149819 File-Format: text/html File-Restriction: Open Access Handle: RePEc:ids:injbaf:v:15:y:2025:i:5:p:1-32