Assistant Professor, School of Management Studies, Sathyabama Institute of Science and Technology , Chennai, Tamil Nadu , India
,
Research Fellow, School of Management Studies, Sathyabama Institute of Science and Technology , Chennai, Tamil Nadu , India
,
Research Fellow, School of Management Studies, Sathyabama Institute of Science and Technology , Chennai, Tamil Nadu , India
,
Research Fellow, School of Management Studies, Sathyabama Institute of Science and Technology , Chennai, Tamil Nadu , India
Research Fellow, School of Management Studies, Sathyabama Institute of Science and Technology , Chennai, Tamil Nadu , India
The fast digitalization of financial services has introduced a new digital lending platform into the financial services market, which is easy to use and fast to provide credit. Circumference of behavioral intention, however, is a key manifestation of the uptake of these services and largely depends on trust, service quality, perceived ease, and perceived risk. The paper will also analyze the aspects that influence consumer acceptance and the subsequent usage of the digital lending applications. To determine the reasons behind the adoption of digital lending platforms, the statistical data were obtained through Cronbach's alpha reliability coefficient and Pearson's correlation coefficient, which were used by those who already used the services of digital lending platforms. The relationships between trust, perceived ease of use, perceived risk, service quality, and intention to use digital lending services were analyzed. The results show that the greatest determinants of the adoption are consumer trust and ease of use, whereas perceived risk influences continued use negatively. The quality of the service is also an important element that determines loyalty and long-lasting interest. This research is a useful contribution to the informational content of fintech firms to improve user experiences, develop trust, and address the perceived risks to further evolve the digital lending services. Real-life constraints are: there must be a geographic focus and use of self-reported information. Future studies can consider cross-country comparison and longitudinal studies, as well as the implementation of AI-based trust systems.
This is an open access article distributed under the Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
0
The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.