Behavioural Drivers of AI-Enabled Fintech Adoption: A Study on Digital Literacy and Investment Intentions of Equity Investors

This study investigates the role of Intention to adapt as a critical element in the adoption of ‎Artificial Intelligence (AI) supported financial technology (FinTech) platforms among equity ‎investors. It advances understanding of how psychological and technological factors jointly ‎shape investor behaviour in an AI-driven equity ecosystem. Specifically, it investigates how ‎digital literacy and perceived risk interact with Intention to invest to influence Intention to adapt ‎and investment decision-making. The required data for the study were collected through an ‎online survey from 233 Gen-Z equity investors. Using Structural Equation Modelling (SEM), ‎the study tested an integrated framework combining the Unified Theory of Acceptance and Use ‎of Technology (UTAUT2) and Behavioural Finance Theory. Reliability and validity were ‎assessed using Confirmatory Factor Analysis (CFA), and the mediation effect was analysed to ‎evaluate the mediating role of Intention to adapt. The study found that digital literacy, perceived ‎risk, and financial well-being significantly impact Intention to adapt, whereas effort expectancy, ‎performance expectancy, and social influence did not. Intention to adapt was also identified as ‎reducing biases among different investors and strengthening the relationship between digital ‎literacy and adoption intention. The proposed model also explained a substantial proportion of ‎the variance in investment decision-making, highlighting the importance of intention-to-adapt-‎driven adoption pathways. These findings suggest that policymakers, FinTech providers, and ‎financial educators prioritize digital literacy initiatives, strengthen data transparency, and embed ‎ethical AI frameworks to improve investor confidence. Furthermore, the work confirms that ‎enhancing Intention to adapt can mitigate perceived risks and raise the long-term adoption rate ‎of AI-enabled financial services‎.

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Publication Details

Journal
International Journal of Accounting and Economics Studies
Published
2025-12-17
DOI
https://doi.org/10.14419/05tcqc37
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
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article

Behavioural Drivers of AI-Enabled Fintech Adoption: A Study on Digital Literacy and Investment Intentions of Equity Investors

K. Shriya, T. Velmurugan
International Journal of Accounting and Economics Studies
FinTech, Crowdfunding, Digital Finance
article

Behavioural Drivers of AI-Enabled Fintech Adoption: A Study on Digital Literacy and Investment Intentions of Equity Investors

K. Shriya, T. Velmurugan
article en

Abstract

This study investigates the role of Intention to adapt as a critical element in the adoption of ‎Artificial Intelligence (AI) supported financial technology (FinTech) platforms among equity ‎investors. It advances understanding of how psychological and technological factors jointly ‎shape investor behaviour in an AI-driven equity ecosystem. Specifically, it investigates how ‎digital literacy and perceived risk interact with Intention to invest to influence Intention to adapt ‎and investment decision-making. The required data for the study were collected through an ‎online survey from 233 Gen-Z equity investors. Using Structural Equation Modelling (SEM), ‎the study tested an integrated framework combining the Unified Theory of Acceptance and Use ‎of Technology (UTAUT2) and Behavioural Finance Theory. Reliability and validity were ‎assessed using Confirmatory Factor Analysis (CFA), and the mediation effect was analysed to ‎evaluate the mediating role of Intention to adapt. The study found that digital literacy, perceived ‎risk, and financial well-being significantly impact Intention to adapt, whereas effort expectancy, ‎performance expectancy, and social influence did not. Intention to adapt was also identified as ‎reducing biases among different investors and strengthening the relationship between digital ‎literacy and adoption intention. The proposed model also explained a substantial proportion of ‎the variance in investment decision-making, highlighting the importance of intention-to-adapt-‎driven adoption pathways. These findings suggest that policymakers, FinTech providers, and ‎financial educators prioritize digital literacy initiatives, strengthen data transparency, and embed ‎ethical AI frameworks to improve investor confidence. Furthermore, the work confirms that ‎enhancing Intention to adapt can mitigate perceived risks and raise the long-term adoption rate ‎of AI-enabled financial services‎.

International Journal of Accounting and Economics StudiesVol. 12(8)
SRM Institute of Science and Technology (IN)
Openalex Percentile: Top 42%
FinTech, Crowdfunding, Digital Finance
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