Regulating Robo Advice for Consumers' Financial Decisions: The Interplay between AI Algorithm Quality and Digital Choice Architecture

Document Type

Article

Publication Date

10-29-2024

Abstract

Rapid advances in digital interfaces, the quality of predictive algorithms, and the availability of high-speed internet are allowing firms to offer robo-advice: automated online guidance about which financial products are suitable for a consumer. At their best, robo-advisors feature algorithms that accurately predict which financial products are the optimal match for a given consumer’s needs and use digital choice architectures (that is, ways of presenting the product recommendations online) that are designed to strongly guide consumers to those best-fit products. Yet when algorithms lack great accuracy, strong guidance in favor of products incorrectly predicted to have the best fit could lead consumers to select options that do not meet their needs well. The possibility that strong guidance results in different financial outcomes depending on the quality of the algorithms has important implications for regulating robo-advice. We propose that, consistent with current regulatory practice for human advisors, regulators should require any firm wishing to implement a robo-advisor for its clients to demonstrate both that the robo-advisor is honest (that is, it works in the best interests of the client) and that its algorithms meet some established level of accuracy. In addition, regulators should require any firm offering a robo-advisor to demonstrate that the strength of the guidance provided by the digital choice architecture aligns with the predictive accuracy of the advisor’s algorithms. We offer several practical suggestions for implementing such a regulatory strategy. The need for regulations is becoming increasingly urgent because many robo-advisors now use artificial intelligence (AI) to make predictions. AI has made robo-advisors more powerful and easier to use, which is likely to expand their adoption—and, by extension, the harm that would be caused if subpar robo-advisors are allowed on the market.

Keywords

robo-advice, robo-advisor, algorithm, AI algorithm, financial advice, digital choice architecture

Publication Title

Behavioral Science & Policy

Publication Citation

Dellaert, B. G. C., Baker, T., & Johnson, E. J. (2024). Regulating robo-advice for consumers’ financial decisions: The interplay between algorithm quality & digital choice architecture. Behavioral Science & Policy, 10(2), 1-7. https://doi.org/10.1177/23794607241296686

DOI

https://doi.org/10.1177/23794607241296686

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