The Intricate Effects of Complexity and Personalization on Investment Intention in Robo-Advisory

Abstract

Amongst the tremendous transformation of the financial services industry in recent years, robo-advisory has emerged as new technology and proven its potential to digitalize this industry. Robo-advisors grant their users access to wealth management services that were historically performed manually. In doing so, robo-advisors allow personalization of investment portfolios on an unprecedented scale. Simultaneously, investment decisions are inherently complex for average users. Understanding how personalization and complexity affect users is, therefore, crucial for robo-advisors. We examine these effects in an online experiment with a fictitious robo-advisor and 169 participants. Our results show that personalization lowers users’ intention to invest, while complexity has a significant positive effect on users’ investment intentions and attenuates the negative impact of personalization. We contribute to IS research by uncovering the intricate effects of combining complexity and personalization in digital environments that will gain importance with users facing increasingly complex digital products.