Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers
By Daniel Belanche, Luis Vicente Casaló, Carlos Flavián. Industrial management & data systems, 2019
588 citations recorded by the source corpus.
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.
Subfields: Economics and Econometrics, Information Systems and Management, Management Information Systems
View Paper: https://www.semanticscholar.org/paper/f8576d4e9f0b5caf0218e4866dfa095c01e954f3
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In Economics and Econometrics
In Information Systems and Management
- Luis Vicente Casaló
- Daniel Belanche
- Carlos Flavián
- S. K
- Devadas Menon
- Paul Rodway
- Astrid Schepman
- Jeroen J. L. Schepers
In Management Information Systems
Citations in the corpus
- Service robot implementation: a theoretical framework and research agenda (2019, background): “might reject a robo-advisor when they invest vast sums or to obtain a mortgage (Belanche et al., 2019).”
- Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success (2020, background): “Automated agents constitute an entirely new field of research within the domain of service technology (Van Doorn et al., 2017; Belanche et al., 2019).”
- The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence (2022, background): “Individuals who are more familiar with technological innovations may have first-hand access to such technologies, be more aware of the use scenarios and practical values of technologies, and therefore, have a more positive stance toward AI (Belanche et al., 2019; Mantello et al., 2021).”
- “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model (2023, background): “In a prior study on D. Menon and K. Shilpa robo-advisors ’ usage in the banking sector [95], observed that age and gender positively influence the perceived usefulness and user intention to use them.”