Trust in fintech banking: The strategic role of data security in stakeholder confidence

  • 8 Views
  • 1 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Type of the article: Research Article

Abstract
This study examines the impact of fintech usage, accounting knowledge, financial reporting systems, and transparency on stakeholder trust, with banking data security playing a moderating role. Warp PLS was employed to analyze data collected from 231 professional employees of private banks in East Java, Indonesia. The sample was purposefully selected to ensure insights from professionals actively engaged with fintech applications in the banking sector. Respondents were surveyed through structured questionnaires to evaluate their perceptions of fintech integration and its influence on trust-related mechanisms. The study follows strict ethical guidelines to protect human participants and uphold the integrity of the research process. The findings highlight that robust financial reporting systems (β = 0.405, p < 0.001) and transparency (β = 0.336, p < 0.001) significantly enhance stakeholder trust. In contrast, fintech usage (β = –0.010, p = 0.440) and accounting knowledge (β = –0.021, p = 0.370) demonstrated no direct impact. Banking data security was found to positively moderate the relationship between fintech usage (β = 0.169, p = 0.004), financial reporting systems (β = 0.229, p < 0.001), and transparency (β = 0.108, p = 0.047) with stakeholder trust. However, data security did not significantly moderate the effect of accounting knowledge on trust (β = 0.055, p = 0.198), suggesting that stakeholders rely on accounting expertise independent of security measures. These results highlight the importance of prioritizing transparency and data security in banking fintech operations to foster trust among stakeholders in private banks.

view full abstract hide full abstract
    • Figure 1. Research model and hypotheses
    • Figure 2. Outer model
    • Table 1. Formulating a questionnaire
    • Table 2. Respondent characteristics
    • Table 3. Validity and reliability test
    • Table 4. Model fit
    • Table 5. Hypotheses testing results
    • Table A1. Research instrument
    • Table B1. Private banks
    • Conceptualization
      Sasongko Budisusetyo
    • Data curation
      Sasongko Budisusetyo
    • Formal Analysis
      Sasongko Budisusetyo
    • Funding acquisition
      Sasongko Budisusetyo
    • Investigation
      Sasongko Budisusetyo
    • Methodology
      Sasongko Budisusetyo
    • Project administration
      Sasongko Budisusetyo
    • Resources
      Sasongko Budisusetyo
    • Software
      Sasongko Budisusetyo
    • Supervision
      Sasongko Budisusetyo
    • Validation
      Sasongko Budisusetyo
    • Visualization
      Sasongko Budisusetyo
    • Writing – original draft
      Sasongko Budisusetyo
    • Writing – review & editing
      Sasongko Budisusetyo