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ESTD Year: 2017 | Impact Factor: 6.9
DOI Prefix: 10.47001/IRJIET
ESTD Year: 2017 | Impact Factor: 6.9
DOI Prefix: 10.47001/IRJIET
Vol 10 No 8 (2026): Volume 10, Issue 8, August 2026 | Pages: 65-78
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 25-08-2026
This study aims to examine customer perceived quality of AI-driven digital financial service platforms (DFSPs) in Saudi Arabia. The study is grounded in the Technology Acceptance Model (TAM), the DeLone and McLean Information Systems Success Model, and trust theory to establish the study’s constructs. The study developed a structural model comprising seven latent constructs: AI-Driven Service Quality (AISQ), Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Trust in AI (TR), Perceived Risk (PR), Customer Perceived Quality (CPQ), and Customer Satisfaction (CSAT). To test the model, an online survey was conducted with 226 active users of digital financial service platforms in Saudi Arabia. The postulated relationships were examined using covariance-based structural equation modeling (CB-SEM). The results revealed that AI-driven service quality had a positive but nonsignificant direct impact on customer perceived quality, while it had a positive and significant impact on customer satisfaction. Perceived usefulness and trust had positive and significant direct impacts on customer perceived quality, while perceived ease of use influenced customer perceived quality indirectly through perceived usefulness. Perceived risk had a negative but non-significant impact on both customer satisfaction and customer perceived quality. Customer satisfaction partially mediated the relationship between AI-driven service quality and customer perceived quality. A cross-sectional research design is a major limitation of this study because it precludes generalizable conclusions about the dynamic evolution of customers’ perceptions of digital financial services. The study’s conceptual model provides a better understanding of customer-perceived quality of AI-driven in the context of digital financial service platforms. The study’s implications help service providers implement appropriate measures to improve digital financial services and reshape platforms’ quality past AI and emerging technologies.
Artificial Intelligence; Digital Financial Service Platforms; Customer Perceived Quality; Structural Equation Modeling; Saudi Arabia; TAM; Trust; FinTech.
Dr. Abdullah Ali Albinalsheikh. (2026). Customer Perceived Quality of AI-Driven Digital Financial Service Platforms (DFSPs) in Saudi Arabia. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(8), 65-78. Article DOI https://doi.org/10.47001/IRJIET/2026.108008
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