Robo-advisors are a new type of FinTech increasingly used by millennials in place of traditional financial advice. Building on artificial intelligence, robo-advisors provide personalized asset and wealth management services. Their application and study have hitherto focused exclusively on individual advisory regarding asset management. We observe a pressing need to investigate robo- advisors’ application for complex artificial intelligence based recommendation tasks both, in context of group decision-making and in contexts beyond asset management, due to robo-advisors’ potential as a lever for integrating artificial intelligence in the entire decision-making process. Thus, we present a action design research in progress aimed at designing such a robo-advisor. More specifically, this study investigates whether and how robo-advisory promotes consensus-efficient group decision-making in new types of economic scenarios (after-sales). Based on a comprehensive problem formulation, we aim towards deriving a set of meta-requirements and design principles that are embodied in a preliminary prototypical instantiation of a robo-advisor.
Namyslo, Nicole Maria and Jung, Dominik, "Towards Designing Robo-Advisory to Promote Consensus Efficient Group Decision-Making in New Types of Economic Scenarios" (2023). ECIS 2023 Research-in-Progress Papers. 18.