This study identifies and synthesizes patterns and trends in the emerging body of literature of environmental, social, and corporate governance (ESG) endeavors on the financial performance (FP) of the banking firms. It specifically aims to highlight the relationship of ESG–FP. The scoping review analysis is based on 1856 journal articles from two online databases, namely Scopus and Web of Science (WoS) for the period of 2015 to 2023. The analysis reveals inconsistent results regarding the ESG–FP relationship, with some studies reporting positive impacts, others negative, and several showing no significant relationship. Notably, non-linear studies consistently identify an inverted U-shaped relationship, suggesting that there is a threshold level of ESG investment beyond which additional investments do not yield proportional benefits. This indicates that threshold-based policies may be more effective at maximizing ESG benefits. The study also found that numerous studies suggested exploring the indirect effect or mediating variables in the ESG–FP relationship to better explain the FP variance. Thus, the study identifies a need for future research to explore indirect relationships by testing potential moderators or mediators, particularly bank risk-taking, to better understand the ESG–FP dynamics. Policymakers and regulators should adopt non-linear analytical approaches and set threshold-based ESG investment policies, while bank management should strategically invest in ESG activities, integrating ESG considerations into risk management frameworks. Continuous monitoring and evaluation, along with stakeholder engagement, are crucial for optimizing ESG investments. By adopting these strategies, banks can enhance financial performance and contribute to sustainable and responsible banking practices.

This study provides a comprehensive bibliometric analysis of FinTech research spanning from 1968 to 2025, using 2760 articles indexed in the Web of Science database. It aims to uncover major publication trends, core theoretical frameworks, emerging topics, and the intellectual structure of FinTech scholarship. Employing VOSviewer and Harzing’s Publish or Perish software, this study maps co-occurrence networks, citation structures, and thematic clusters. It analyzes document types, source distribution, geographical contributions, keyword evolution, and the top 10 most cited papers in FinTech literature. The analysis reveals a significant surge in FinTech research since 1968, driven by the growing impact of digital finance innovations. The top three countries contributing to FinTech publications are the USA, England, and China. Dominant publication outlets include the International Journal of Bank Marketing and the Journal of Financial Services Marketing. Key research themes have evolved across three distinct periods: early banking and innovation (1968–1999), customer satisfaction and trust (2000–2011), and bank performance and digital adoption (2012–2025). Emerging topics include blockchain, mobile banking, crowdfunding, and Internet banking. The Technology Acceptance Model (TAM), along with its extended versions (TAM2, TAM3, UTAUT), is identified as the foundational theoretical framework in this field. The co-citation and keyword cluster analysis confirm the centrality of trust, risk, satisfaction, and performance in shaping FinTech outcomes. These findings not only synthesize FinTech’s academic development but also inform future research by identifying intellectual gaps and high-impact trends. The study highlights the growing integration between FinTech and consumer behavior and calls for deeper exploration into regulatory, ethical, and cybersecurity issues affecting FinTech adoption. Beyond the banking sector, the thematic patterns uncovered particularly in areas such as blockchain-based supply chain finance, crowdfunding ecosystems, and AI-enabled embedded financial services signal substantial strategic implications for non-financial firms. These include enhanced liquidity management, decentralized capital access, and data-driven business model innovation across diverse industries such as manufacturing, retail, and digital commerce.

This study evaluates how ESG strategic intensity and AI capability shape risk-adjusted lending performance in ASEAN-5 banks, grounding the model in the Resource-Based View (RBV) and Institutional Theory to explain how internal capabilities and external regulatory forces interact. Using a cross-sectional survey of 486 banking professionals from 62 listed commercial banks across Indonesia, Malaysia, the Philippines, Singapore, and Thailand, relationships were estimated via PLS-SEM with standard robustness checks, including multicollinearity, reliability, validity, and predictive relevance, while mediation and moderation were assessed through bootstrapped indirect effects and interaction terms. The results show that ESG strategic intensity directly improves risk-adjusted lending performance, while AI capability influences performance only indirectly. Both ESG and AI strongly enhance credit-risk discipline, which itself is a key driver of lending performance. ESG retains a direct path to performance while also working through credit-risk discipline, its effect reflects partial mediation. In contrast, the effect of AI operates entirely through credit-risk discipline, indicating full mediation. Regulatory pressure strengthens the influence of both ESG and AI on credit-risk discipline, demonstrating that stricter supervisory environments amplify the translation of sustainability and technological capabilities into more disciplined lending practices. These findings underscore CRD as the operational hinge through which sustainability and digital capabilities are converted into superior lending outcomes, highlighting the importance of governed data pipelines, explainable risk models, and effective early-warning mechanisms, supported by aligned managerial incentives and supervisory expectations. At the societal level, disciplined ESG- and AI-enabled lending reduces information frictions, supports equitable credit access for credible SMEs and households, stabilizes credit cycles, and mitigates adverse selection when paired with safeguards on privacy, transparency, and bias control. Overall, the study offers an integrated, theory-driven, institution-level assessment of how ESG and AI capabilities translate into measurable performance within a multi-country ASEAN context, clarifying when and how strategic and regulatory forces jointly improve credit outcomes.

This study investigates the extent to which Generation Z employees’ preferred work types, namely, remote work, hybrid arrangements, flexible hours, and on-site settings influence their intention to remain within small- and medium-sized enterprises (SMEs) in Malaysia. Central to this inquiry is the mediating role of perceived autonomy in shaping this relationship. Drawing upon a quantitative, cross-sectional survey design, data were collected from a sample of 256 Gen Z employees across various Malaysian SMEs. The analytical framework employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine both direct and mediated effects. The findings reveal that all four work type preferences exert significant influence on both perceived autonomy and retention intention, with hybrid work emerging as the most impactful configuration. Furthermore, the mediation analysis establishes that perceived autonomy partially mediates the relationship between preferred work types and employee retention, underscoring its function as a pivotal psychological mechanism that connects structural workplace features to behavioral outcomes. This study represents one of the earliest empirical contributions to the literature by examining how the alignment between work preferences and autonomy perceptions affects Gen Z retention within the context of emerging-market SMEs. The findings yield actionable implications for SME leaders, emphasizing the importance of designing hybrid and autonomy-enhancing work environments to foster long-term organizational commitment among younger workforce cohorts.

This study examines how AI-enabled risk analytics capability, digital leadership orientation, and regulatory support and clarity jointly shape bank financial performance in ASEAN-5, addressing a key gap in prior work that has typically treated technological, organizational, and regulatory enablers in isolation and rarely integrated the Technology-Organization-Environment framework with the Resource-Based View and Dynamic Capabilities Theory in an emerging, bank-based context. Using survey data from 385 banking professionals across ASEAN-5 and Partial Least Squares Structural Equation Modelling, the study models FinTech adoption as a mediating dynamic capability linking these enablers to performance. The results show that all three antecedents significantly enhance both FinTech adoption and bank financial performance, with adoption exerting the strongest direct effect and partially mediating each relationship. The study contributes by theorizing AI-enabled risk analytics and digital leadership as strategic resources whose value is amplified when embedded in supportive regulatory environments and operationalised through FinTech adoption. The findings imply that ASEAN banks can strengthen profitability and efficiency not by isolated technology investments, but by aligning AI capabilities, leadership agendas, and regulatory clarity around coherent digital adoption strategies, offering actionable insights for managers and regulators seeking to close digitalisation gaps while safeguarding performance.