建议(编程)
行为经济学
激励
公共经济学
经济
债务
轻推理论
投资(军事)
面子(社会学概念)
消费(社会学)
行为经济学
财务
营销
微观经济学
业务
心理学
社会心理学
政治学
社会学
计算机科学
政治
社会科学
程序设计语言
法学
作者
Francesco D’Acunto,Alberto G. P. Rossi
标识
DOI:10.1146/annurev-financial-110921-013217
摘要
Robo-advice uses big and open data to provide consumers with fully informed and rational-expectation benchmarks in all realms of household finance, including consumption, saving, investment, and debt management choices. It also minimizes the monetary, cognitive, and psychological costs that households face in economic transactions. We review recent research on the features and effects of robo-advice on individual and aggregate economic outcomes through the lens of its differences from traditional human advice. We discuss the distributional implications of robo-advice, its potential role in increasing the effectiveness of economic policies, the role of providers’ incentives, and several questions that are still wide open for researchers in finance, economics, social psychology, and related fields.
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