Trust in fintech banking: The strategic role of data security in stakeholder confidence
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DOIhttp://dx.doi.org/10.21511/bbs.20(4).2025.12
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Article InfoVolume 20 2025, Issue #4, pp. 138-152
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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.
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JEL Classification (Paper profile tab)G21, G28, M15, M41
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References32
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Tables7
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Figures2
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- Figure 1. Research model and hypotheses
- Figure 2. Outer model
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- 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
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