To FinTech and Beyond

Goldstein, Itay; Jiang, Wei; Karolyi, G. Andrew

doi:10.1093/rfs/hhz025

Cited by 417 publications

(198 citation statements)

References 11 publications

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“…Overall, our study suggests the existence of a barrier for the adoption of innovative financial technologies (FinTech; e.g., Goldstein et al, 2019). While robo-advisors can often be accessed more easily now via smartphonessimilarly to any other mobile financial service (e.g., Luarn & Lin, 2005;Malaquias & Hwang, 2016;Yen & Wu, 2016) our findings suggest that many people might still be reluctant to use such services, due to machines' lack of legitimacy to make decisions with a moral component (Bigman et al, 2019;Bigman & Gray, 2018).…”

Section: Discussionmentioning

confidence: 78%

Robo-investment aversion

Niszczota¹,

Kaszás²

2020

Preprint

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In three experiments (N = 2380), we show that people find it more permissible when investment decisions concerning controversial (“sin”) stocks are made by human fund managers rather than by computers (“robos”). In Study 1 (N = 466), participants rated the permissibility of a computer (algorithm) to autonomously exclude morally controversial stocks from investment portfolios as lower than if a human fund manager did the same; this finding was not different if participants were informed that such exclusions might be financially disadvantageous for them. In Study 2 (N = 1231), we show that this robo-fund aversion manifests itself both when considering investment in controversial and non-controversial industries. In Study 3 (N = 683), our findings show that robo-fund aversion is also present when algorithms are given the autonomy to increase investment in controversial stocks. Our findings suggest that algorithm aversion extends to the financial realm, supporting the existence of a barrier for the adoption of innovative financial technologies (FinTech), but one that might be overcome by hybrid (human-in-the-loop) solutions.

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Section: Discussionmentioning

confidence: 78%

Robo-investment aversion

Niszczota¹,

Kaszás²

2020

Preprint

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“…5 Blockchains are validated and updated within peer-to-peer networks using a 'consensus mechanism' (for example "proof of work" or "proof of stake", see Tschorsch and Scheuermann 2016) that prevents members of the network from creating a false version of history. This consensus then supports a fully decentralized secure verification of ownership and exchange (Pilkington 2016;Goldstein et al 2019). In the case of Bitcoin, the term block was originally used because its consensus mechanism ('mining') is applied to append 'blocks' of around 1000 transactions at a time to the chain of transaction records.…”

Section: Introductionmentioning

confidence: 66%

Cryptocurrencies: market analysis and perspectives

2019

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The papers in this special issue focus on the emerging phenomenon of cryptocurrencies. Cryptocurrencies are digital financial assets, for which ownership and transfers of ownership are guaranteed by a cryptographic decentralized technology. The rise of cryptocurrencies' value on the market and the growing popularity around the world open a number of challenges and concerns for business and industrial economics. Using the lenses of both neoclassical and behavioral theories, this introductory article discusses the main trends in the academic research related to cryptocurrencies and highlights the contributions of the selected works to the literature. A particular emphasis is on socio-economic, misconduct and sustainability issues. We posit that cryptocurrencies may perform some useful functions and add economic value, but there are reasons to favor the regulation of the market. While this would go against the original libertarian rationale behind cryptocurrencies, it appears a necessary step to improve social welfare.

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“…Overall, our study suggests the existence of a barrier for the adoption of innovative financial technologies (FinTech; e.g., [ 56 ]; however, see [ 21 ] for an alternative account). While investors today enjoy an unprecedented ease of access to financial products and services, they might still be reluctant to use them.…”

Section: Discussionmentioning

confidence: 94%

Robo-investment aversion

Niszczota

Kaszás

2020

PLoS ONE

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In five experiments ( N = 3,828), we investigate whether people prefer investment decisions to be made by human investment managers rather than by algorithms (“robos”). In all of the studies we investigate morally controversial companies, as it is plausible that a preference for humans as investment managers becomes exacerbated in areas where machines are less competent, such as morality. In Study 1, participants rated the permissibility of an algorithm to autonomously exclude morally controversial stocks from investment portfolios as lower than if a human fund manager did the same; this finding was not different if participants were informed that such exclusions might be financially disadvantageous for them. In Study 2, we show that this robo-investment aversion manifests itself both when considering investment in controversial and non-controversial industries. In Study 3, our findings show that robo-investment aversion is also present when algorithms are given the autonomy to increase investment in controversial stocks. In Studies 4 and 5, we investigate choices between actual humans and an algorithm. In Study 4 –which was incentivized–participants show no robo-investment aversion, but are significantly less likely to choose machines as investment managers for controversial stocks. In contrast, in Study 5 robo-investment aversion is present, but it is not different across controversial and non-controversial stocks. Overall, our findings show a considerable mean effect size for robo-investment aversion ( d = –0.39 [–0.45, –0.32]). This suggests that algorithm aversion extends to the financial realm, supporting the existence of a barrier for the adoption of innovative financial technologies (FinTech).

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To FinTech and Beyond

Cited by 417 publications

References 11 publications

Robo-investment aversion

Robo-investment aversion

Cryptocurrencies: market analysis and perspectives

Robo-investment aversion

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