With the rapid growth of digital payment solutions in Switzerland, customer support is experiencing not only a higher volume of inquiries but also an increase in their complexity. Traditional service channels can struggle to keep pace with these demands while simultaneously meeting strict security and regulatory standards. To maintain a competitive edge, ensure high service quality, and provide fast, reliable assistance, UBS TWINT needs to evaluate innovative technologies such as Generative AI as a means to enhance efficiency, scalability, and the overall customer experience.

This study applied a structured mixed-methods approach, combining expert interviews, customer surveys, and analysis of relevant operational processes. It examined potential AI application areas, levels of user acceptance, expected efficiency gains, and key regulatory aspects. In addition, best practice examples and UBS’s existing AI capabilities were reviewed. All findings were consolidated into a comprehensive recommendation report, serving as a strategic basis for UBS TWINT’s potential future integration of Generative AI.

The research shows strong customer openness to AI-assisted support, particularly for straightforward and repetitive inquiries. Generative AI offers the potential to shorten response times, improve service consistency, and free human agents for complex cases. Successful deployment requires a phased introduction, starting with low-risk use cases, supported by strong data governance and compliance with Swiss data protection laws. The final product of this thesis is a detailed recommendation report, outlining strategic steps, compliance measures, and operational guidelines to support UBS TWINT in assessing and preparing for possible integration of Generative AI into its support framework. By combining innovation, trust, and customer focus, the report serves as a foundation for strengthening UBS TWINT’s position in the competitive digital payments market.