The integration of Artificial Intelligence (AI) in the banking sector has redefined traditional relationship banking by enabling personalized, efficient, and data-driven customer interactions. This study examines the effectiveness of AI-enabled relationship banking through the lenses of emotional intelligence and customer trust. It explores how AI technologies—such as chatbots, virtual assistants, and predictive analytics—replicate emotionally intelligent behaviors to enhance customer experience.

The research focuses on understanding the extent to which AI systems can interpret and respond to customer emotions, thereby influencing satisfaction, engagement, and loyalty. Furthermore, it evaluates the role of customer trust as a key determinant in the adoption and success of AI-driven banking services. Factors such as perceived empathy, transparency, data privacy, and reliability are analyzed to assess their impact on trust formation.

Adopting a quantitative research approach, data were collected from banking customers through structured questionnaires and analyzed using statistical techniques. The findings reveal that while AI significantly enhances service efficiency and personalization, its effectiveness in relationship banking is largely dependent on its ability to simulate emotional intelligence and foster trust. The study concludes that banks must integrate emotionally responsive AI systems and maintain ethical standards to strengthen customer relationships and ensure sustained engagement in the digital era.

Keywords

Artificial Intelligence, Relationship Banking, Emotional Intelligence, Customer Trust, Customer Satisfaction, Digital Banking, AI Chatbots, Customer Engagement