Algorithm Aversion als Hindernis bei der Etablierung von Robo Advisors

Abstract

Within the framework of an economic laboratory experiment, we investigate how Algorithm Aversion impedes the establishment of Robo Advisors. The participants have to cope with diversification tasks. They can do this themselves or they can entrust a Robo Advisor with this task. The Robo Advisor evaluates all relevant data and always makes the decision that leads to the highest expected value of compensation for the participant. Although the high performance of the Robo Advisor is obvious, the participants only trust the Robo Advisor in around 40% of all decisions. This reduces their success and their compensation. Many participants are guided by the 1/n heuristic, which contributes to their suboptimal decisions. Insofar as the participants have to decide for others, they noticeably put more effort into it and are also more successful than when they decide for themselves. However, this does not affect the acceptance of the Robo Advisor. Even in the case of proxy decisions, the Robo Advisor is only used in around 40% of cases. The propensity of economic agents towards algorithm aversion stands in the way of a broad establishment of Robo Advisors.