Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/216621
Authors: 
D'Acunto, Francesco
Rossi, Alberto G.
Year of Publication: 
2020
Series/Report no.: 
CESifo Working Paper 8225
Abstract: 
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.
Subjects: 
FinTech
behavioral economics
algorithmic advice
A1
financial regulation
financial literacy
JEL: 
D14
G21
Document Type: 
Working Paper

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