Abstract
Automated financial advising (robo-advising) has become an established practice in wealth management, yet very few studies have looked at the cross-section of the robo-advisors and the factors explaining the persistent variability in their portfolio allocation recommendations. Using a sample of 53 advising platforms from the US and Germany, we show that the underlying algorithms manage to identify different risk profiles, although substantial variability is evident even within the same investor types' groups. The robo-advisor expertise in a particular asset class seems to play a significant role, as does the geographical location, while the breadth of the offered investment choice (number of portfolios) across the robo-advisors under study does not seem to have an effect.
Highlights
IntroductionThe financial industry experienced some radical changes
Over the last decade, the financial industry experienced some radical changes
The wealth management industry has undergone a transformation driven by technology, but there has been a change in terms of demand that caused the overall increase of assets under management and the emergence of new players
Summary
The financial industry experienced some radical changes. Following the financial crisis of 2007, increased regulatory burdens on incumbents and wide adaptations of new technologies led to the emergence of a new structure, where some of the areas are dominated by smaller, more efficient start-ups that use internet, blockchain, and social media to create new products for consumers. Technological transformation is evident when it comes to wealth management, retail banking, payments, and lending (Metha et al, 2019). The wealth management industry has undergone a transformation driven by technology, but there has been a change in terms of demand that caused the overall increase of assets under management and the emergence of new players. As Blackrock’s (2015) highlighted, the demand for financial advice has increased along with the household’s level of cash, people’s increased longevity, income gaps caused by retirement, and a general lack of financial literacy
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