We document five effects of providing individuals with crowdsourced spending information about their peers (individuals with similar characteristics) through a FinTech app. First, users who spend more than their peers reduce their spending significantly, whereas users who spend less keep...

Consumers might overestimate optimal spending if forming beliefs based on others' spending, because others' conspicuous consumption is more visible than the rest of their consumption. If true, information about others' overall spending should change beliefs and choice. For a test, we provide...

We document five effects of providing individuals with crowdsourced spending information about their peers (individuals with similar characteristics) through a FinTech app. First, users who spend more than their peers reduce their spending significantly, whereas users who spend less keep...

We study a robo-advising portfolio optimizer that constructs tailored strategies based on investors' holdings and preferences. Adopters are similar to non-adopters in terms of demographics, but have more assets under management, trade more, and have higher risk-adjusted performance. The...

In this chapter, we first discuss the limitations of traditional financial advice, which led to the emergence of robo-advising. We then describe the main features of robo-advising and propose a taxonomy of robo-advisors based on four defining dimensions - personalization, discretion,...

In this chapter, we first discuss the limitations of traditional financial advice, which led to the emergence of robo-advising. We then describe the main features of robo-advising and propose a taxonomy of robo-advisors based on four defining dimensions---personalization, discretion,...

We study a robo-advising portfolio optimizer that constructs tailored strategies based on in- vestors' holdings and preferences. Adopters are similar to non-adopters in terms of demographics, but have more assets under management, trade more, and have higher risk-adjusted performance. The...

We document that, since 2011, mortgage lenders reduced credit to middle-class households by 15% and increased credit to wealthy households by 21%. Credit to low-income households was unaffected. Results hold at the individual-loan level and zip-code level, and at the intensive margin and...