Working Paper

Robo-Advising

Francesco D'Acunto, Alberto G. Rossi
CESifo, Munich, 2020

CESifo Working Paper No. 8225

In this work, we first discuss the limitations of traditional financial advice, which led to the emergence of robo-advising. We then describe the main features of robo-advising and propose a taxonomy of robo-advisors based on four defining dimensions---personalization, discretion, involvement, and human interaction. Building on these premises, we delve into the theoretical and empirical evidence on the design and effects of robo-advisors on two major sets of financial decisions, that is, investment choices (for both short- or long-term horizons) and the allocation of financial resources between spending and saving. We conclude by elaborating on five broadly open issues in robo-advising, which beget theoretical and empirical research by scholars in economics, finance, psychology, law, philosophy, as well as regulators and industry practitioners.

CESifo Category
Behavioural Economics
Economics of Digitization
Keywords: FinTech, behavioral economics, algorithmic advice, A1, financial regulation, financial literacy
JEL Classification: D140, G210