1. Adam Grealish 1. is head of investments at Altruist in Los Angeles, CA. (agrealish{at}gmail.com) 2. Petter N. Kolm 1. is a clinical full professor and director of the Mathematics in Finance Master’s Program at New York University’s Courant Institute of Mathematical Sciences in New York, NY. (petter.kolm{at}nyu.edu) <!-- --> 1. To order reprints of this article, please contact David Rowe at d.rowe{at}pageantmedia.com or 646-891-2157. Over the past decade robo-advisors have gone from offerings from a handful of start-ups to an established and fast-growing segment of the wealth management industry. Robo-advisors use technology to translate core retail investing principles—establishing an investment plan, seeking broad diversification, weighting cost and value, and accounting for taxes—into automated platforms with easy-to-use interfaces. Intuitive user experience backed by well-established investment processes allow individual investors to create and execute investment strategies with little or no interaction with a financial professional, resulting in large economies of scale for robo-advisors and low costs for clients. In this article, the authors discuss how robo-advisors assess client risk tolerance, build, and recommend portfolios, manage risk, and optimize taxes. They discuss the implementation of goal-based investing, socially responsible (ESG) investing, and smart beta strategies on robo-advisory platforms. Additionally, they examine robo-advisor performance during the market downturn in March 2020, the first significant market drawdown since their introduction, and find portfolio performance in agreement with broadly diversified stock and bond holdings. Consistent with expectations, robo-advisors also reported increased tax-loss harvesting activity during this downturn. Key Findings