Abstract
This study aimed to explore how financial technology companies employed dark patterns to influence investors’ financial decision-making and behavior. We examined 26 mobile apps that are available in Norway and allow users to purchase stocks, funds, and cryptocurrencies. Our goal was to identify any design strategies that may be deemed unethical. We detected several methods or deceptive tactics deliberately devise to evade the purpose of GDPR. Nearly all the studied apps incorporate dark patterns to varying degrees, and the manipulation level using these practices differs between bank and non-bank apps. Banks have more transparent apps with fewer dark patterns. They give more importance to safeguarding users’ personal information than non-bank fintech companies and are less likely to exploit the data shared by users. Non-bank apps display more intrusive data policies and subpar default settings than banks. They utilize deceptive practices to conceal pricing, encourage user interaction, and dissuade users from exiting the platform.
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References
Bösch, C., Erb, B., Kargl, F., Kopp, H., Pfattheicher, S.: Tales from the dark side: privacy dark strategies and privacy dark patterns. Proc. Priv. Enhancing Technol. 2016(4), 237–254 (2016)
Brignull, H.: Deceptive design. https://www.deceptive.design/. Accessed 20 Mar 2023
Conti, G., Sobiesk, E.: Malicious interface design: exploiting the user. In: Proceedings of the 19th International Conference on World Wide Web, North Carolina, USA, pp. 271–280. ACM (2010). https://doi.org/10.1145/1772690.1772719
Di Geronimo, L., Braz, L., Fregnan, E., Palomba, F., Bacchelli, A.: UI dark patterns and where to find them: a study on mobile applications and user perception. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–14. ACM (2020). https://doi.org/10.1145/3313831.3376600
Finansportalen. https://www.finansportalen.no/plassere-penger/. Accessed 22 Feb 2022
Gray, C.M., Kou, Y., Battles, B., Hoggatt, J., Toombs, A.L.: The dark (patterns) side of UX design. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–14. ACM (2018). https://doi.org/10.1145/3173574.3174108
Lewis, C.: Monetary dark patterns. In: Irresistible Apps, pp. 111–117. Apress, Berkeley, CA (2014). https://doi.org/10.1007/978-1-4302-6422-4_10
Mathur, A., et al.: Dark patterns at scale: findings from a crawl of 11K shop** websites. In: Proceedings of the ACM on Human-Computer Interaction (CSCW), vol. 3, pp. 1–32. ACM (2019). https://doi.org/10.1145/3359183
Neste Bank. https://nestebank.no/banker/. Accessed 22 Feb 2022
Rakovic, I: Dark finance: exploring deceptive design in investment apps. Master’s Thesis, NTNU (2022)
Soe, T.H., Nordberg, O.E., Guribye, F., Slavkovik, M.: Circumvention by design - dark patterns in cookie consent for online news outlets. In: Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Sha** Experiences, Sha** Society, pp. 1–12. ACM (2020). https://doi.org/10.1145/3419249.3420132
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This paper was based on the master’s thesis of the first author conducted under the direction of the second author.
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Appendix
Appendix
A dark pattern taxonomy developed based on the most cited papers of literature.
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Rakovic, I., Inal, Y. (2023). Dark Finance: Exploring Deceptive Design in Investment Apps. In: Abdelnour Nocera, J., Kristín Lárusdóttir, M., Petrie, H., Piccinno, A., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2023. INTERACT 2023. Lecture Notes in Computer Science, vol 14142. Springer, Cham. https://doi.org/10.1007/978-3-031-42280-5_20
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