Design Patterns of Investing Apps and Their Effects on Investing Behaviors

Generative AI (Text, Image, Music, Video)Algorithmic Transparency & AuditabilityConsumers & ShoppersPersonal Finance Users

Smartphone apps such as Robinhood and Public that promise to "democratize investing'' have risen in popularity over the past few years. These apps allow retail investors, who often possess little prior investing experience, to trade stocks, options, and other securities easily and inexpensively, often commission-free. It seems plausible that the interaction patterns of these new apps may significantly influence trading behaviors of their users. But so far, there is little formal design guidance on how such apps should be designed. This paper introduces a set of design guidelines for encouraging healthy investing behaviors by drawing on three bodies of related work: 1) findings from finance and economics literature on healthy investment practices, 2) the dual process theory from behavioral sciences, and 3) design metaphors used in interfaces with uncertain rewards. Using these guidelines, we qualitatively analyze the user interfaces of some popular investment platforms. Our analysis reveal that, unfortunately, popular trading apps generally do not follow design patterns that encourage healthier trading behaviors. We discuss design implications and opportunities for future design.

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https://hci.top/en/papers/dis/60202/2021

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DOI: https://dl.acm.org/doi/10.1145/3461778.3462008
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Source
DIS
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Year
2021
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2 authors
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Subtopics
Generative AI (Text, Image, Music, Video), Algorithmic Transparency & Auditability
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Consumers & Shoppers, Personal Finance Users
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Abstract only
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1 related papers