With the accelerating digital transformation of the financial industry, FinTech innovations have reshaped traditional banking structures by introducing new technological capabilities, service delivery mechanisms, and competitive dynamics. As banks increasingly integrate FinTech solutions into their operational and strategic processes, they encounter a broad set of risks that stem from technological complexity, regulatory uncertainty, cybersecurity vulnerabilities, and evolving customer expectations. These risks, if not properly identified and managed, can adversely affect financial stability, operational continuity, and institutional reputation. In emerging economies such as Iran, where digital transformation in banking is rapidly expanding, risk assessment becomes even more critical due to infrastructural constraints, regulatory gaps, and the heterogeneous maturity of financial technologies. Motivated by these challenges, this study conducts a comprehensive evaluation of major risks associated with FinTech adoption in Iranian banks, employing neutrosophic multi-criteria decision-making (MCDM) techniques to capture uncertainty, ambiguity, and expert judgment variability during risk assessment process.
Introduction
In recent years, the emergence of financial technologies (FinTech) has transformed the banking industry by enabling innovative financial services, reshaping business models, and changing customer expectations. While FinTech offers greater accessibility and efficiency, it also introduces new challenges for financial institutions, including heightened competitive pressure and disruptions to traditional banking operations. Although many studies highlight the positive contribution of FinTech to banking performance, others emphasize the potential negative consequences, such as reduced profitability due to competition from digital lending and investment platforms. In addition, risks such as cybersecurity threats, regulatory compliance issues, operational failures, data privacy concerns, technological dependency, and challenges in customer trust have become major barriers to FinTech adoption. Given these complexities, a systematic and structured assessment of FinTech-related risks is essential, particularly in developing countries where digital transformation is rapidly progressing but regulatory and infrastructural limitations persist. This study seeks to address this research gap by offering a comprehensive, uncertainty-aware evaluation of the critical risks influencing FinTech adoption in banks.
Methodology
This study adopts a hybrid neutrosophic multi-criteria decision-making (MCDM) framework to identify, validate, and prioritize key risks associated with FinTech adoption. First, an extensive literature review was conducted to extract potential risk factors highlighted in previous academic and industry reports. Next, the neutrosophic Delphi method was applied to refine and validate these factors based on expert consensus under uncertainty. Through this process, seven major risks were confirmed: security, credit, operational, strategic and competitive, legal and regulatory, reputational, and liquidity risks. Subsequently, the neutrosophic Best–Worst Method (BWM) was employed to determine the relative importance of these risks, enabling more accurate modeling of expert judgment hesitation and ambiguity. Finally, to evaluate potential FinTech implementation options for Pasargad Bank, the neutrosophic Multi-Attributive Border Approximation Area Comparison (MABAC) method was used. This integrated approach makes it possible to capture the complexity and uncertainty inherent in technological risk assessment.
Results and Discussion
The results of the BWM analysis indicate that security risk holds the highest importance in the context of FinTech adoption, reflecting the increased sensitivity of digital transactions and the potential for cyberattacks, data breaches, and system intrusions. Operational and reputational risks ranked next, underscoring the significance of system reliability and customer trust in digital financial environments. These findings are consistent with existing studies that emphasize the dominant role of cybersecurity threats in shaping FinTech outcomes.
In terms of implementation strategies, the MABAC analysis reveals that the scenario involving collaboration among banks to form a FinTech consortium holds the highest priority. This strategy supports resource sharing, cost reduction, and the development of standardized and secure financial technologies. Moreover, it enables banks to pool expertise and strengthen resilience against technological and regulatory uncertainties. For Pasargad Bank, the results suggest that focusing on robust security practices, operational risk management, and reputation preservation is essential to ensuring successful and low-risk FinTech implementation. The findings also align with international evidence indicating that collaborative and partnership-based FinTech models yield more sustainable and resilient outcomes in uncertain environments.
Conclusion
This study contributes to the FinTech risk literature by providing a structured and uncertainty-aware assessment of the major risks influencing FinTech adoption in banking. The proposed hybrid neutrosophic MCDM framework—combining Delphi, BWM, and MABAC—offers a more realistic modeling environment for capturing ambiguity, incomplete information, and expert hesitation. According to the results, security risk represents the most critical concern for banks in their FinTech implementation efforts, followed by operational and reputational risks. The findings also highlight the strategic value of interbank collaboration, suggesting that forming a FinTech consortium is the most advantageous and least risky implementation scenario for Pasargad Bank.
The insights from this study have practical implications for bank managers and policymakers. Banks should establish specialized FinTech risk management units, invest in advanced cybersecurity infrastructure, strengthen digital operational capabilities, and enhance customer awareness programs. Furthermore, closer engagement with regulators is required to ensure compliance and foster a supportive regulatory environment. Future research may expand this study by incorporating time-series data on risk events, exploring emerging technologies such as AI and blockchain, and conducting comparative analyses across multiple banks or countries to develop more generalizable insights.