Risk profiling question investigation for robo-advisor

Abstract

Purpose – this study aims to thoroughly investigate by reviewing previous literature on risk assessment queries for robo-advisors, comparing it with three existing robo-advisors and proposing suitable risk assessment questions for robo-advisor. Research methodology – utilize the deductive content analysis technique to examine the risk assessment issue for financial robo-advisors, which is influenced by previous study. Findings – there are nine questions share a similar context both in previous literature and among existing robo-advisors, with income being the most commonly used question. Then, there are three questions that are only asked by the existing robo-advisors: emergency funds, home ownership, and the source of transaction. These findings suggest some additional questions to enhance the effectiveness of risk assessment in robo-advisory services for individuals. Research limitations – only two previous research papers have focused on risk profiling, and three available applications used in this research. Practical implications – the robo-advisor’s developer should take into account various factors such as local culture and economic conditions, financial product knowledge, etc. when crafting diverse risk profiles to provide more precise investment recommendations. Originality/Value – the study is the first research which explore the risk profiling for financial robo-advisor, which used by existing robo-advisor then compared to other countries in the world.