• Project Period: 07/2020 - 06/2023
• Project Partners: LIT Robopsychology Lab, Raiffeisenlandesbank OÖ

Artificially intelligent finance-apps on cell phones or service robots in bank branches: The digital transformation has already arrived in the banking sector and progressively affects its customers. Standardized customer inquiries can increasingly be outsourced to machines, and automated data analyses allow more individualized consulting services.

But how far should the technological development of service communication go from the perspective of bank customers? In what areas of application are robots and bots acceptable, where does interpersonal communication remain indispensable? How can the different expectations and needs of different customer groups be best addressed?

These questions are the focus of a new research cooperation between the Innovation Hub of the Raiffeisenlandesbank Oberösterreich and the LIT Robopsychology Lab at JKU Linz. At the core of the project "Banking Bots" stands the perspective of users. Within the framework of several technological-psychological studies, the conditions under which machine dialog systems in physical customer contact (e.g., information robots in the branch) or in digital customer contact (e.g. finance bot, chatbot, avatar) encounter with user acceptance and what advantages or disadvantages are expected from the use of such new technologies, will be jointly researched over a period of three years. In particular, individual needs and individual differences in requirement preferences are dealt with, for example comparing between more or less technically experienced groups of people. In view of the many different possibilities for the bank-specific employment of robots and bots, also situation and context-dependent acceptance differences will be determined.

Research results from the project "Banking Bots" will help to obtain a more detailed picture of customer attitudes towards automated communication and advisory services in the bank’s customer service and will facilitate empirically sound decisions about their future use.