Robo Advice and Access to Wealth Management

85 Pages Posted: 28 Jan 2020 Last revised: 14 Jan 2023

See all articles by Michael Reher

Michael Reher

University of California, San Diego (UCSD) - Rady School of Management

Stanislav Sokolinski

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick

Date Written: October 29, 2022

Abstract

We examine how access to automated wealth managers affects household investment and
welfare across the wealth distribution. Our setting features novel microdata from a major
U.S. robo advisor and a quasi-experiment in which the advisor reduces its account minimum
by 90%. Based on a difference-in-difference estimator, the reduction significantly increases
middle-class households’ participation but does not affect wealthier or poorer households. We
rationalize this behavior with a quantitative model calibrated using portfolio-level data. The
reduction raises welfare through diversification, priced risk exposure, and personalization. The
overall welfare gains are moderate but heterogeneous. Older households with weak earnings
growth gain most.

Keywords: FinTech, Financial Advice, Portfolio Delegation, Inequality

JEL Classification: G11, G24, D3, O3

Suggested Citation

Reher, Michael and Sokolinski, Stanislav, Robo Advice and Access to Wealth Management (October 29, 2022). Available at SSRN: https://ssrn.com/abstract=3515707 or http://dx.doi.org/10.2139/ssrn.3515707

Michael Reher (Contact Author)

University of California, San Diego (UCSD) - Rady School of Management ( email )

9500 Gilman Drive
Rady School of Management
La Jolla, CA 92093
United States

Stanislav Sokolinski

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick ( email )

111 Washington Avenue
Newark, NJ 07102
United States

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