Analyzing Investor Behavior through the Use of Fintech in Iranian Private Banks
Keywords:
Private banks, Financial decision-making improvement, Financial decision-making, FintechAbstract
This study aims to develop a comprehensive conceptual model of investor behavior in interaction with financial technologies (fintech) in Iranian private banks. This research is qualitative in nature and employs a thematic analysis approach. Data were collected through in-depth semi-structured interviews with 17 experts in banking and fintech, selected using purposive (snowball) sampling. The data analysis process involved open, axial, and selective coding and was conducted using MAXQDA software. Data credibility was ensured through theoretical saturation, expert validation, and iterative analysis. The findings indicate that five core themes—digital transformation in banking services, enhancement of trust and data security, digital investor behavior analysis, data-driven decision-making, and development of digital financial human capital—significantly shape investor behavior. Results further reveal that the interaction between big data analytics and behavioral biases critically determines financial decision quality, while trust in technology functions as a mediating variable enhancing the impact of other factors. The study concludes that successful fintech implementation in private banks requires an integrated approach combining technological, behavioral, and institutional dimensions; beyond digital infrastructure development, reengineering technological culture and improving digital financial literacy are essential prerequisites for enhancing investor decision-making.
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Copyright (c) 2025 Samira Dosti Gofli, Hoda Hemmati, Davood Hemmati, Mehdi Fathabadi (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
