This investigation extends into the intricate fabric of customer-based corporate reputation within the banking industry, applying advanced analytics to decipher the nuances of customer perceptions. By integrating structural equation modeling, particularly through SmartPLS4, we thoroughly examine the interrelations of perceived quality, competence, likeability, and trust, and how they culminate in customer satisfaction and loyalty. Our comprehensive dataset is drawn from a varied demographic of banking consumers, ensuring a holistic view of the sector’s reputation dynamics. The research reveals the profound influence of these constructs on customer decision-making, with likeability emerging as a critical driver of satisfaction and allegiance to the bank. We also rigorously test our model’s internal consistency and convergent validity, establishing its reliability and robustness. While the direct involvement of Business Intelligence (BI) tools in the research design may not be overtly articulated, the analytical techniques and data-driven approach at the core of our methodology are synonymous with BI’s capabilities. The insights garnered from our analysis have direct implications for data-driven decision-making in banking. They inform strategies that could include enhancing service personalization, refining reputation management, and improving customer retention efforts. We acknowledge the need to more explicitly detail the role of BI within the research process. BI’s latent presence is inherent in the analytical processes employed to interpret complex data and generate actionable insights, which are crucial for crafting targeted marketing strategies. In summary, our research not only contributes to academic discourse on marketing and customer perception but also implicitly demonstrates the value that BI methodologies bring to understanding and influencing consumer behavior in the banking sector. It is this blend of analytics and marketing intelligence that equips banks with the strategic leverage necessary to thrive in today’s competitive financial landscape.

The banking sector is a pillar of the world’s economic fabric and is today facing a major revolution due to the demands of sustainable development objectives and the evolution of sustainable finance tools. This article analyses the impact of green credit on commercial banks’ performance based on data from 10 commercial banks in China between 2012 and 2022. The study found that in the short term, the implementation of green credit has a positive effect on the income level of commercial banks’ intermediate activities and a moderating effect on their return on total assets and non-performing loan ratio.

There is fast growth of digital banking services in Saudi Arabia clearly shows the necessity of well-considered legal decisions. However, there is an obscurity with respect to protecting consumers’ rights and creating a reliable atmosphere for digital finance through legal framework in the digital banking sector in the Kingdom. The primary aims and objectives of this research is to scrutinize the digital banking consumers’ protection legal framework being overseen in Saudi Arabia, analyzing its content, mechanisms, and impact on different stakeholders. Similarly, the study tires to determine its efficacy as well as identify the roadblocks which can prevent its success. Through an extensive review and examination, the evaluation defines key issues, difficulties and finalizes statements about the legal field. The content analysis methodology was used to help address issues emanating from the existing literature. Various scholarly articles, policy documents, and regulatory guidelines were explored. In other words, data for this study were collected through different search sources such as journals, traditional articles of Google Scholar, policy documents, and library sources. A total of 25 articles were explored and contributed immensely to unveiling various aspects of the legal framework of digital banking as well as consumers’ protection in the Kingdom. The findings of this investigation have identified three basic themes on the domestic legal regulation of consumers’ protection in the digital banking system in Saudi Arabia. First, the study has analyzed various legislations such as: consumer protection law, sector-specific regulations, among others concerning the rights and duties of consumer protection. Second, legal obligations in seeking remedies when there is a discriminatory treatment in digital banking services. Third, it has been established that Saudi Arabia have taken a proactive step towards a robust safety cushion to protect the consumer rights and minimizing the risks involved in cybersecurity in the context of Saudi Arabia. Theoretically, on one hand, the study highlights the paramount significance to consumers’ protection legislations in the Kingdom. On the other hand, practically, the Kingdom’s witness of rapid economic growth and technological advancement, ensuring robust consumer protection measures becomes increasingly paramount to foster trust, promote fair business practices, and enhance consumer confidence in the marketplace. Nonetheless, some limitations such as insufficient consumers’ education and regulatory inadequacies were noted which need national coordination between stakeholders. Notwithstanding the fact that the legal framework exhibits strong points especially in addressing vital issues, its timely evaluation, amendment, and enforcement is deemed as a key to solve the emerging challenges and obtain confidence of consumers when it comes to digital banking.

Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.

Loans are a critical transmission channel for commercial banks as well as an important revenue source. Macroeconomic factors are not within the control of commercial banks, however, select factors are observed to have a direct impact on lending behaviour in studies around the world. This study examined the relationship between macroeconomic variables and the lending behaviour of banks in South Africa for the period ranging from 2001 to 2022. Quarterly time series data was employed using the Autoregressive Distributed Lag Model (ARDL). The empirical results of the paper revealed that there is a long-run relationship between the repurchase rate (repo rate), inflation, the real effective exchange rate (REER) and lending behaviour in South Africa. The REER and inflation were both found to have a positive relationship, whilst the repo rate had a negative relationship. In addition, Gross Domestic Product (GDP), the activity rate and sovereign credit rating (SCR) changes returned insignificant results. Overall, these findings show that select macroeconomic factors do influence lending behaviour in South Africa. Furthermore, the results suggest that monetary policy decisions have a direct influential effect on lending and the South African Reserve Bank (SARB) has implemented their policies effectively.

Customers are displaying heightened awareness and involvement in their banking arrangements, and they are actively assessing and remembering information to make informed decisions regarding the allocation of their financial resources towards environmental protection solutions such as clean energy, sustainable construction, climate change control and social protection. Based on the current theoretical gap of factors influencing customer satisfaction and thereby encouraging continued engagement in green finance initiatives, this study aims to identify the factors influencing customer satisfaction as a means of fostering greater participation in green finance amongst customers of commercial banks in Ho Chi Minh City. Using data from a survey of 479 individuals who are customers at commercial banks in Ho Chi Minh City, this study analyses and evaluates the impact of factors influencing customer satisfaction and the role of customer satisfaction in green finance continuance behaviour. Combining basic analysis techniques in quantitative research such as statistics, evaluation of Cronbach’s alpha reliability, exploratory factor analysis (EFA), measurement models and Partial Least Squares structural equation modelling (PLS-SEM) from SPSS and SMART PLS software. the results of this research indicate that: (1) Green Banking initiative (GB), Information Support (IS) and Emotional Support (ES) positively impact Customer Satisfaction (SA); (2) Customer Satisfaction (SA) positively impacts Green Finance Continuance Behaviour (GF).