## The Intersection of FinTech Adoption and Its Role in the Banking Sector### AbstractThe adoption of financial technology (FinTech) and the development of human resource (HR) competencies, service innovation, and firm growth are crucial for the expansion of the banking sector. However, obtaining reliable results can be challenging due to intricate correlations among these characteristics. This study introduces a hybrid multi-criteria decision-making (MCDM) model that uses the Entropy-Weighted Method (EWM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Our goal is to assess and rank multiple alternatives systematically based on important criteria using EWM-TOPSIS approaches. Specifically, we analyze eleven multifaceted characteristics and eight options (A1 to A8), revealing the benefits of the presented MCDM approaches in determining FinTech adoption, HR competency, service innovation, and firm growth. Our findings demonstrate that entropy-TOPSIS approaches can provide valuable insights for smarter decision-making. Ultimately, our research identifies the best alternative among the evaluated options, contributing to a better understanding of FinTech, HR competency, service innovation, and firm growth in the banking sector.### Impact of FinTech Adoption on Service Innovation, HR Competency Potential, and Firm Growth in the Banking Sector**Introduction**In today's digital landscape, businesses must embrace digitalization. Using modern systems (e-banking), banks introduce alternative service channels while cutting costs by reducing branch offices and staff. The digitalization of banking services has become evident through advancements in IT infrastructure, facilitating the banking sector's shift toward technological modifications. Banking institutions seek innovation to address shortcomings in post-crisis scenarios and disrupt conventional approaches. FinTech innovations and HR competency potential have gained prominence in banking, providing sophisticated methods to engage customers and gather data for lending decisions and streamlining customer-related issues.**The Need for Multi-Criteria Decision-Making (MCDM) in Banking**Evaluating FinTech adoption, HR competency potential, service innovation, and firm growth in banking is complex. This study presents a comprehensive MCDM model combining EWM and TOPSIS to solve this multi-criteria challenge and sequence the options for effective decision-making in the banking sector. EWM determines criterion importance, while TOPSIS ranks the selected options. The best option is chosen, and an efficient decision is made.**Role of FinTech, HR Competency, Service Innovation, and Firm Growth in the Banking Sector**FinTech adoption, service innovation, and HR competency potential influence banking efficiency and growth. FinTech provides innovative techniques for improved customer engagement and risk management. HR competency potential enhances employee skills and productivity, while service innovation caters to changing customer demands. These factors contribute to firm growth and profitability in the banking sector.**Methodology**The proposed MCDM model incorporates:* EWM for determining criterion importance* TOPSIS for ranking alternatives* Eleven criteria and eight alternatives* Numerical calculations using entropy and TOPSIS**Results**The analysis revealed alternative A6 as the top performer, excelling in FinTech adoption, HR competency, service innovation, and firm growth. Conversely, alternative A7 exhibited the lowest performance.**Discussion and Conclusion**This study addressed methodological gaps in evaluating FinTech adoption, HR competency potential, service innovation, and firm growth in the banking sector. The MCDM approach provided a systematic assessment framework for decision-makers. The results highlight the significance of hybrid MCDM techniques in evaluating these factors and identify the most impactful alternative (A6) for the banking sector. Alternative A6 leverages advanced technologies and strategic partnerships to enhance customer experiences, reduce costs, and drive growth.**Limitations and Future Research*** Not all criteria may be covered by the defined standards* The dynamic nature of FinTech requires regular reevaluations of weights and standards* Expanding the dataset to include diverse institutions and analyzing the integration of emerging technologies like blockchain**Significance*** Provides a practical MCDM framework for evaluating FinTech adoption and its impact on banking* Assists bankers and investors in making informed decisions* Facilitates the selection of the most effective alternative for the banking sector's growth and efficiency* Contributes to the advancement of FinTech and HR competency in the banking industry* Highlights the significance of sustainable practices and innovation for financial institutions