Financial advice and discretion limits

Abstract

Biased recommendations from financial advisors often lead to suboptimal portfolios and unnecessary fees. In response, many households have moved to digital platforms, so-called "robo-advisors," that provide low-fee financial advice based on the household's observable characteristics. We model the advisorclient relationship and show that delegation with limits on the advisor's choice set (i.e., discretion limits) reduces the negative consequences of biased recommendations. Moreover, our analysis suggests that human advisors may play an important role in financial advice when they possess soft information about the client. The analysis suggests that a hybrid solution consisting of discretion limits (produced by a robo-advisor-like platform) and advisor choice may be optimal.

Who uses Robo-Advisors? The Polish Case

“…Importantly, how knowledge about remote consultancy is obtained may affect how it is received and, consequently, trust in robo-advisory services. Moreover, human advisors may play a vital role in financial advice when they possess "soft" information about the client (Davies, 2020).…”

Advertising exposure and investor attention: Estimates from Super Bowl commercials

“…Lastly, in regard to the field of financial planning, our findings about the effect of the Super Bowl commercials on investor attention could be useful for financial advisors interested in nudging their clients towards saving more, since it might be easier for them to suggest an investment in a stock which the client is already considering. In other words, knowing the commercials to which clients are exposed is soft information that could be a valuable item in an advisor's toolkit (e.g., Davies, 2020).…”