Regulatory Nudges and Investor Protection in China’s Robo-Advisory: Behavioral Insights for Policy Design
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The algorithmic service model of robo-advisors poses challenges to the traditional legal regulatory framework. The traditional regulatory concept clings to the “rational person hypothesis”, ignoring investors' cognitive biases and behavioral irrationality, and is compounded by multiple mismatches at the institutional level. Behavioral economics, based on the assumptions of bounded rationality and the social person, helps social individuals correct their cognitive and behavioral biases through nudging regulation. Therefore, the design of the regulatory nudging scheme for robo-advisors should follow the concept of soft paternalism, guiding social individuals to make decisions through non-mandatory interventions. Specifically, it is necessary to construct a classification standard for investors, establish a trading cooling-off period system, improve the information disclosure system, and strengthen relevant investor education. In this way, the regulation of robo-advisors can be transformed from static control to dynamic adaptation, seeking the harmonious unity of financial technology and financial regulation.
Abstract
The algorithmic service model of robo-advisors poses challenges to the traditional legal regulatory framework. The traditional regulatory concept clings to the “rational person hypothesis”, ignoring investors' cognitive biases and behavioral irrationality, and is compounded by multiple mismatches at the institutional level. Behavioral economics, based on the assumptions of bounded rationality and the social person, helps social individuals correct their cognitive and behavioral biases through nudging regulation. Therefore, the design of the regulatory nudging scheme for robo-advisors should follow the concept of soft paternalism, guiding social individuals to make decisions through non-mandatory interventions. Specifically, it is necessary to construct a classification standard for investors, establish a trading cooling-off period system, improve the information disclosure system, and strengthen relevant investor education. In this way, the regulation of robo-advisors can be transformed from static control to dynamic adaptation, seeking the harmonious unity of financial technology and financial regulation.