Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 7 June 2019
Issue publication date: 18 September 2019
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.
Keywords
Citation
Belanche, D., Casaló, L.V. and Flavián, C. (2019), "Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers", Industrial Management & Data Systems, Vol. 119 No. 7, pp. 1411-1430. https://doi.org/10.1108/IMDS-08-2018-0368
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited