LAUSR

Abstract Recently, Digital Financial Advice Solutions (i.e., “Robo Advice” or “Robo Advisory”) are emerging rapidly within the financial services sectors, which can be outlined by the respective Assets under Managements’ CAGR of 255.9 % from 2016 to 2018 in Germany (Kaya, 2019). However, these developments imply both opportunities and threats for traditional financial institutions: On the one hand, potential customer out-migrations, the loss of cross-selling potentials and potential yields as well as challenged competitiveness pose significant risks. On the other hand, if traditional banks manage to implement appropriate measures timely, the recent developments also offer great market potentials. Thus, it is inevitable to identify, understand and discuss factors that drive the customers’ future usage intention of Digital Financial Advice Solutions. As a result, we derive, from the traditional financial institutions’ point of view, strategic and managerial implications on how to deal with the currently emerging trends of Digital Financial Advice Solutions. For this purpose, we conducted a questionnaire-based online survey, which ultimately led to 600 evaluable observations. Finally, according to the two strands of literature this study bases on, i.e., the Net Valence Framework and Unified Theory of Acceptance and Use of Technology 2, we built a partial least squares (PLS)-based structural equation model (SEM) 1 that incorporates a comprehensive set of variables. In doing so, we contribute to not only the general understanding of Digital Financial Advice Solutions and two different strands of literature but also to the solution of issues that are of great relevance for practitioners, too. Subsequently, this study concludes by the derivation of future research requirements regarding these, both theoretically and practically, important matters.