Artificial intelligence in banking: The factors shaping social robot relationships
In this article, Meral Ahu Ozcan Karageyim, Senior Researcher at CARF, dives into how AI and social robots are changing the way we experience banking. She explores the tech, psychology, and human factors that shape trust, engagement, and the future of customer interactions in finance.
In this article, Meral Ahu Ozcan Karageyim, Senior Researcher at CARF, dives into how AI and social robots are changing the way we experience banking. She explores the tech, psychology, and human factors that shape trust, engagement, and the future of customer interactions in finance.
The Fourth Industrial Revolution has introduced a wave of transformative technologies that are reshaping everyday life. Artificial intelligence has moved beyond experimental applications and is now deeply embedded in almost every domain of modern life. Education, entertainment, retail, finance, investment, and the broader service sector increasingly rely on AI-driven systems to improve efficiency, accuracy, and personalization. Digital assistants such as Siri and Alexa exemplify how AI simplifies everyday tasks, enabling users to access information, manage schedules, and control smart environments with minimal effort. The global market size for service robots is expected to reach approximately $799 million by 2031, underscoring the growing economic significance of these technologies.
More advanced AI applications are emerging in the form of social robots—machines designed to interact with humans in socially meaningful ways. These robots are no longer confined to laboratories. In cities such as Seoul, service robots guide customers to restaurant tables and assist elderly individuals in their homes. In Tokyo, AI-powered robots support customers in bank branches, handling inquiries that were traditionally managed by human employees.
In the era of generative AI, customers show a growing preference for effortless and largely invisible interactions rather than traditional digital banking experiences. Platforms such as Uber, Booking.com, and Starbucks illustrate this shift by embedding financial services directly into user journeys, reducing friction and enhancing convenience.
As social robots become more common across industries, their integration into banking appears inevitable. However, adoption depends on specific psychological, technological, and relational factors.
Key themes for the adoption of social robots in banking
Academic research on social robots in banking primarily focuses on the relationship between consumers and intelligent machines. Besides technical features such as design, customer-related characteristics such as age, gender, wealth, and financial literacy play an important role.
Findings consistently highlight several key themes that shape adoption:
• Social interaction characteristics, including liveliness, perceived humanity, social intelligence, and capacity to respond
• Customer responses, such as satisfaction, comfort, and emotional reactions during interactions
• Perceptions of the company or brand, influenced by the use of advanced technologies
• Previous familiarity with self-service technologies, which lowers resistance to AI-based services
• Technology anxiety and the need for human interaction, which can hinder adoption
• Anthropomorphism, which fosters social presence and likeability
• Trust as an important factor for giving sensitive data
• Speed, convenience, and perceived ease of use.
Social presence refers to the extent to which a technology conveys a sense of human-like interaction. This capability is central to the effectiveness of social robots, as it shapes how users perceive credibility, empathy, and engagement during interactions. In addition to these relational factors, functional attributes such as speed, convenience, and perceived ease of use play a critical role in encouraging acceptance.
Trust emerges as a particularly important factor in financial contexts. Because social robots often handle sensitive personal and financial data, concerns related to privacy and security significantly influence customer attitudes. Empirical studies generally provide strong evidence for the acceptability of social robots in the financial services industry, provided that trust is established and maintained.
Artificial intelligence and social robots are no longer futuristic concepts; they are active agents reshaping service ecosystems today. In banking and finance, their adoption reflects broader changes in technology, consumer expectations, and organizational strategy. As AI continues to evolve, the successful integration of social robots will depend on balancing efficiency with trust, automation with social presence, and innovation with customer needs. The financial institutions that manage this balance effectively are likely to shape the future of service delivery in the digital age.
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