Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advice

Abstract Adaptive online platforms, powered by artificial intelligence, commonly referred to as robo-advice, steadily increase their market share. Yet these comparably new financial services are critically understudied. Little is known about why some investors adopt robo-advice for something essential asset allocation. The current paper tries close this gap shedding light on the causal effect of investor overconfidence propensity using robo-advice. study proposes a theoretical framework that combines divergence opinion hypothesis with consumer behavior insights and information technology diffusion research. empirically tested Investor Sample 2015 National Financial Capability Study, subsample 2000 US investors. results from series generalized linear, structural, semiparametric models show in pre-chasm market, overconfident have significantly higher adopting While literacy seems decrease uptake, unjustified confidence one’s knowledge causally increases it. Willingness take risk cannot account increased adoption among findings help managers better position offering behavioral into user base. In addition, outline managerial tool demand-side actions likelihood an end-user innovation crossing chasm.