Purpose:


Start-ups, particularly those operating in the fintech sector, have emerged in recent years as influential and transformative players in financial systems. By leveraging emerging technologies, these firms have disrupted traditional financial services and opened new pathways for service delivery, customer acquisition, and value creation. However, innovation in business models, environmental uncertainty, and the lack of transparent performance histories pose substantial risks to investing in fintech ventures. The financing of these companies is primarily undertaken by venture capital institutions. One of the major concerns of these institutions is the absence of a structured, comprehensive, and context-sensitive framework tailored to the unique characteristics of fintech firms for investment assessment. This study aims to design a systematic and multi-dimensional evaluation framework for accurately assessing fintech investment opportunities using a data-driven approach to enhance decision-making.


Methodology:


This research was conducted using a multi-phase mixed-methods approach. In the first phase, a meta-synthesis method was employed to systematically review 77 academic and research-based sources to identify the key assessment factors. In the second phase, semi-structured interviews were conducted with 10 experts in the fields of venture capital, fintech, and technological entrepreneurship. The collected data from both phases were coded and analyzed using thematic analysis, resulting in the identification of 178 basic themes, 22 organizing themes, and 8 global themes. In the final phase, to explore causal relationships among the identified dimensions and determine their influence and dependence levels, the DEMATEL method and a pairwise comparison questionnaire were utilized. The analyses were validated through expert participation and focus group discussions to ensure the content validity of the resulting framework.


Findings:


The analysis led to the development of a comprehensive framework comprising eight main dimensions: financial, corporate governance, technical, competitive, human resources, legal, founders, and infrastructure. The analysis of causal relationships among these dimensions revealed that “founders” and “human resources” are the most influential dimensions, playing a central role in the success of fintech investments. Conversely, the “financial” dimension demonstrated the highest dependence, significantly affected by the quality of other components. This indicates that an exclusive focus on financial indicators during early-stage evaluations does not offer a complete picture of a fintech firm’s potential, and greater emphasis should be placed on human and technological aspects.


Conclusion:


The proposed framework offers a practical and decision-support tool for venture capitalists, accelerators, and institutions operating within the innovation and entrepreneurship ecosystem. By providing a holistic and data-informed view, the model enables investors to make more intelligent and insightful decisions based on a deeper understanding of success drivers and risk factors. Additionally, the framework can serve as a basis for developing early-stage screening tools and decision support systems during pre-investment stages. Ultimately, it contributes to reducing uncertainty and enhancing the effectiveness of investment processes in fintech firms. From a broader perspective, the findings also provide a foundation for future research in the field of financial innovation assessment.