Applying EASTL ethical constructs in AI-driven CRM: the mediating role of sustainable customer trust in enhancing customer retention in private sector banks
Aug 2026· Frontiers in Artificial Intelligence· Vol 9· 0 citations· 48 references
Medicine
TL;DR
Investigating ethical AI practices and its impact on Customer Retention and its influence from the one-sided effect shows that ethical AI is not only a compliance obligation, but a strategic lever for building trust and long-term customer relationships.
Abstract
The rapid integration of Artificial Intelligence (AI) in banking, Customer Relationship Management (CRM) has undergone several changes, which have also led to ethical concerns and implications on customer outcomes. While previous studies have studied AI adoption and trust independently, little attention has been placed on how ethical AI dimensions interact and affect customer retention via trust mechanisms. In this sense the objective of our study is to investigate ethical AI practices (using the EASTL framework) and its impact on Customer Retention (CR), with Sustainable Customer Trust (SCT) as mediator factor in private sector banks. A quantitative research design was taken by implementing structured questionnaires for 361 respondents. The model consists of five major ethical AI constructs-Normative Ethical Alignment, Institutional Accountability Mechanisms, Algorithmic Transparency and Explainability, Data Security and Privacy, and Regulatory and Social Legitimacy. The data were processed by Partial Least Squares Structural Equation Modeling (PLS-SEM) to calculate the direct and indirect relationships. The model accounts for 48.4% for Variance in Sustainable Customer Trust and 32.1% for Customer Retention. Algorithmic Transparency, Data Security, Institutional Accountability and Regulatory Legitimacy are the major factors that directly and indirectly affect customer retention via trust suggesting partial mediation. But Normative Ethical Alignment was not significant. Sustainable Customer Trust formed a vital mediating factor of ethical AI practices on the customer retention and its influence from the one-sided effect. The research shows that ethical AI is not only a compliance obligation, but a strategic lever for building trust and long-term customer relationships. These results present useful insights for banks and policymakers into how to develop open and trustworthy AI systems that are responsible and reliable to instill customer trust and sustainability within digital banking environments.
The growing integration of Artificial Intelligence (AI) in Human Resource (HR) analytics has transformed
organizational decision-making processes, creating new opportunities for efficiency, accuracy, and strategic workforce
management. However, the increasing reliance on AI-supported HR systems has also raised concerns regarding employee
trust, transparency, and ethical governance. This study aims to analyse the influence of AI-driven HR analytics on employee
trust within organizations, examine the role of transparency in shaping employee trust toward AI-supported HR decisionmaking, and evaluate the contribution of ethical governance practices in strengthening employee trust in AI-driven HR
analytics. Grounded in HR Analytics Models, Trust Theory, the Organizational Trust Model of Mayer, Davis, and
Schoorman, and Stakeholder Theory, the study adopts a quantitative research approach using primary data collected from
employees across various organizations. The findings are expected to demonstrate that transparent AI processes and robust
ethical governance mechanisms positively influence employee trust and acceptance of AI-supported HR practices. The study
contributes to the growing literature on AI-enabled human resource management by highlighting the importance of
responsible AI implementation and trust-building mechanisms. The findings offer practical implications for organizations
seeking to balance technological innovation with ethical responsibility and employee confidence in AI-driven HR systems.
Manasa P., M. P· International Journal of Inn...· 1 citation
The integration of Artificial Intelligence (AI) in Islamic banking presents unique challenges regarding technological acceptance and religious adherence. This study investigates the impact of AI transparency and perceived Shariah compliance on customer satisfaction, examining the mediating role of customer trust within the digital Islamic finance context. Adopting a quantitative, cross-sectional research design, data were collected from 412 retail customers who had actively used AI-powered banking services within the preceding six months. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the proposed conceptual model. Results indicate that both AI transparency (β = 0.185, p < 0.001) and perceived Shariah compliance (β = 0.248, p < 0.001) significantly enhance customer satisfaction. Furthermore, customer trust serves as a significant partial mediator, channeling the effects of AI transparency (indirect effect = 0.129, p < 0.001) and Shariah compliance (indirect effect = 0.157, p < 0.001) toward satisfaction. The structural model explains 54% of the variance in customer satisfaction and 48% in customer trust. These findings contribute to the literature by integrating technological adoption frameworks with Maqasid al-Shariah and validating trust as a psychological mechanism in algorithmic Islamic finance. Practically, the study underscores the necessity for Explainable AI (XAI) and proactive Shariah governance in AI development to foster cognitive and affective trust, thereby enhancing customer satisfaction in digital Islamic banking.
Rubi Naz, Mufti Aziz Ur Rehman, Asiya Khattak· Journal of Global Social Tra...· 0 citations
Background The digitalization of the banking sector has led to the development of electronic customer relationship management (e-CRM) from a mere transaction portal to a more interactive and conversation-based ecosystem. However, there is a significant gap between algorithm efficiency and maintaining long-term customer engagement. Based on AI-based e-CRM, Sociotechnical Systems theory, Relationship Marketing theory, and Service-Dominant logic, this study examines the structural impact of AI Conversational Interactivity (a hallmark of e-CRM technology capability) on customer engagement, adoption resilience, and continuance intention. Methods This study specifically explores how the interactive front-end of e-CRM triggers consumer resource utilization and uses DART parameters to initiate dual-path trust processing as a human factor in e-CRM. This model is empirically tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) on 400 active users of digital banking services. Results The results indicate that conversational interactivity plays a significant role in building cognitive and affective trust, enabling cognitive economy and providing emotional buffers, respectively. These trust pathways play a crucial role in mediating the relationship between interactive front-end and customer behavioral engagement. The findings further indicate that, Switch Point Optimization Efficacy, which demonstrates the competency of hybrid organizations in managing the transition from AI to human advisors, emerges as a key service recovery tool that moderates the path from trust to adoption, thereby protecting relational equity and preventing value destruction at algorithmic failure points. Conclusions This research presents a strategic guide for e-CRM implementation in financial institutions. The analysis finds that sustainable competitive advantage in maintaining customer engagement lies not in automation, but rather in the proper governance of affective trust toward AI in e-CRM.
Purpose: This study examines how AI-enabled banking interactions influence customer trust and whether data privacy disclosure strengthens this relationship among SeaBank users in DKI Jakarta, Indonesia. Design/methodology/approach: Drawing on the Stimulus-Organism-Response (S-O-R) framework and Social Identity Theory, the study employed an explanatory quantitative design. Data were collected through a structured online questionnaire from 180 active SeaBank depositors aged 18-35 years who had used AI-supported banking features at least three times in the previous three months. The data were analyzed using Ordinary Least Squares (OLS) regression and Moderated Regression Analysis (MRA). Findings: The results demonstrate that AI-enabled interaction has a positive and significant effect on customer trust, while data privacy disclosure also directly enhances trust. More importantly, the interaction term is positive and significant, indicating that transparent privacy disclosure strengthens the relationship between AI-enabled interaction and customer trust. The moderated model explains 56.4% of the variance in customer trust, with the interaction term adding 8.2% incremental explanatory power. Originality/value: This study advances digital banking trust literature by showing that AI-enabled service quality alone is insufficient to generate trust. In an emerging-market context, algorithmic convenience must be accompanied by visible, understandable, and controllable privacy disclosure. The findings extend the S-O-R framework by conceptualizing privacy disclosure as a trust-enabling boundary condition and offer actionable guidance for digital banks seeking to transform privacy governance into a competitive advantage.
Natalia Ayu, Erny Sulistyaningsi, Basneldi Basneldi et al.· JMET: Journal of Management...· 0 citations
Abstract: The banking sector, relies heavily on regulatory compliance and ethical practices, being a corner stone of economic stability to build and sustain customer relationships. In the banking sector the combined impact of employee’s ethics and regulatory compliance on customer satisfaction and retention was studied. This study provides an integrated analysis to address the existing research gap while prior research has largely explored these variables independently.Using a structured questionnaire primary data were collected from 80 respondents based on 5-point Likert scale. To analyse the relationships among variables statistical tools including correlation, regression and ANOVA were employed. A significant positive association between customer outcomes such as trust, satisfaction and loyalty and ethical practices reveal under the study. Notably, regulatory compliance demonstrates a stronger and statistically significant influence on customer satisfaction (β = 0.285, p = 0.016) compared to individual employee ethics.The findings show that employee ethics function as baseline expectations for customers while they are essential such as honesty, confidentiality and fairness. A more critical role in shaping customer perceptions and enhancing trust played by institutional factors like adherence to regulatory guidelines. In the banking industry this highlights the growing importance of “Compliance Branding” as a strategic tool.To achieve long-term customer retention and competitive advantage in the banking sector the study concludes that banks should prioritize robust compliance mechanisms alongside fostering and ethical organizational culture. Through an integrated ethics-compliance framework these findings provide valuable insights for banking professionals and policymakers in strengthening customer relationships.Keywords: Banking Ethics, Regulatory Compliance, Customer Satisfaction, Customer Retention, Indian Banking Sector
Renuka Morani· Journal of Global Economics· 0 citations
Grounded in stakeholder and signaling theories, this study aims to investigate the relationships among responsible artificial intelligence (AI), technological responsibility and customer loyalty among student-digital banking users in Nigeria. It also explores the mediating role of digital trust in these relationships.
This study adopted a quantitative approach, collecting data through a structured questionnaire administered to digitally active student-bank customers from four Nigerian universities. A total of 421 valid responses were analyzed using partial least squares structural equation modeling.
The findings reveal that technological responsibility significantly enhances digital trust but does not exert a direct influence on customer loyalty. In contrast, responsible AI demonstrates a significant positive effect on both digital trust and customer loyalty. Digital trust is a strong predictor of customer loyalty, playing a critical role in fully mediating the relationship between technological responsibility and customer loyalty, and partially mediating the relationship between responsible AI and customer loyalty.
These results suggest that customers perceive responsible AI as a more salient and experience-driven aspect of digital banking than general technological responsibility. The study contributes to the growing literature on corporate digital responsibility by empirically distinguishing responsible AI from broader technological practices and by providing evidence from an emerging economy context. Practical implications for digital banking strategy and ethical AI governance are discussed.
A. G. Agu, N. Madichie, Clara Margaça et al.· Society and Business Review· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
