Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers

Artificial Intelligence in FinTech 5 (2019)
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Abstract

Purpose – Considering the increasing impact of Artificial Intelligence (AI) on financial technology (FinTech), the purpose of this paper is to propose a research framework to better understand robo-advisor adoption by a wide range of potential customers. It also predicts that personal and sociodemographic variables ( familiarity with robots, age, gender and country) moderate the main relationships. Design/methodology/approach – Data from a web survey of 765 North American, British and Portuguese potential users of robo-advisor services confirm the validity of the measurement scales and provide the input for structural equation modeling and multisample analyses of the hypotheses. Findings – Consumers’ attitudes toward robo-advisors, together with mass media and interpersonal subjective norms, are found to be the key determinants of adoption. The influences of perceived usefulness and attitude are slightly higher for users with a higher level of familiarity with robots; in turn, subjective norms are significantly more relevant for users with a lower familiarity and for customers from Anglo-Saxon countries. Practical implications – Banks and other firms in the finance industry should design robo-advisors to be used by a wide spectrum of consumers. Marketing tactics applied should consider the customer’s level of familiarity with robots. Originality/value – This research identifies the key drivers of robo-advisor adoption and the moderating effect of personal and sociodemographic variables. It contributes to understanding consumers’ perceptions regarding the introduction of AI in FinTech.

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Artificial Intelligence in Finance and Investments.Narendra Rao Tadapaneni - 2019 - International Journal of Innovative Research in Science, Engineering and Technology 9 (5).

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Artificial Intelligence in Finance and Investments.Narendra Rao Tadapaneni - 2019 - International Journal of Innovative Research in Science, Engineering and Technology 9 (5).

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