The structural model of startup valuation with a focus on fintech startups

Farmahini Farahani, Sedighe; Khamseh, Abbas; Bayat Tork, Amir

doi:10.22034/jvcbm.2024.449609.1345

The structural model of startup valuation with a focus on fintech startups

Document Type : Original Article (Mixed)

Authors

sedighe farmahini farahani ¹

Abbas Khamseh ²

Amir Bayat Tork ³

¹ Graduated in Technology Management, Department of Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

² Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj, Iran

³ Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

https://doi.org/10.22034/jvcbm.2024.449609.1345

Abstract

Abstract
The purpose of this research is to provide a model for determining the value of startups, focusing on fintech startups. The existing literature lacks models that integrate both quantitative and qualitative dimensions for fintech, which highlights the necessity of conducting this research. This research is applicable in terms of purpose, descriptive-analytical in nature, and mixed (qualitative-quantitative) in terms of type. In the qualitative part, by using the theme analysis technique and interviews with 11 startup investment and valuation experts who were selected by purposive sampling, the main and secondary themes were extracted using MAXQDA software. In the quantitative part, based on the identified themes, a questionnaire with 199 questions was designed and distributed to the statistical population consisting of 220 managers, experts, founders and managers of fintech startups, using available sampling method. The data were analyzed using confirmatory factor analysis by partial least squares method in Smart-PLS software. The final findings included 194 extracted codes in 24 sub-themes and 6 main themes, which in order of importance are business enterprise, environmental factors, technology and innovation, risks, business team, and financial industry. It was found from the results that the valuation of startups in the fintech field is very important for different stakeholders. Therefore, it is imperative to develop comprehensive valuation models that are specifically designed for the unique characteristics of fintech startups. These models should integrate both quantitative measures and qualitative factors to provide a comprehensive assessment of startup value.
Introduction
The valuation of startups is very important for various stakeholders, including founders, investors, employees, and even legislators. According to the National Association of American Startups in 2022, more than 60% of startups failed due to lack of sufficient financing. In addition, according to the report of the Organization for Economic Cooperation and Development in 2023, fintech startups in the member countries of this organization have accounted for 18% of venture investments (OECD, 2023). These statistics and figures show that the accurate valuation of startups, especially in the field of fintech, is of great importance.
Only 28% of fintech companies have managed to achieve a market value of more than one billion dollars (CB Insights, 2021). This statistic shows that existing valuation methods may be insufficient in accurately estimating the growth potential and true value of fintech startups. While important steps have been taken in understanding the valuation of startups, there is a significant research gap, especially regarding fintech startups (Wallace, 2022).
Previous researches have mainly focused on conventional valuation methods applicable to general startup contexts, without paying attention to the distinctive features and nuances of fintech venture valuations (Muchtar et al., 2023).
This research seeks to fill the identified research gap by developing a structural model of startup valuation with a focus on fintech startups. The main question of the current research is: what are the dimensions and indicators affecting the value of fintech startups?
Theoretical Framework
Startup
Startups are entrepreneurial ventures characterized by innovative ideas, agility and the pursuit of growth in a dynamic market environment. These startups are often founded by individuals or small teams with innovative visions that seek to address unmet needs or disrupt existing markets with new solutions (Oliva & Kotabe, 2019). The key feature of startups is their risky nature, limited resources, and emphasis on their scalability. Startups usually operate in sectors ranging from technology and health to finance (Aldianto et al., 2021).
Fintech
Fintech, short for financial technology, refers to the integration of technology into financial services to simplify processes, increase efficiency, and improve the customer experience. Fintech companies use advanced technologies such as artificial intelligence, big data analytics, and cloud computing to provide innovative solutions that challenge traditional financial institutions (Mention, 2019).
Fintech startups
Fintech startups focus on using technology to provide innovative financial products or services. These startups operate at the intersection of finance and technology with the aim of addressing the inefficiencies of traditional financial systems or introducing completely new business models (Zarrouk et al., 2021). Fintech startups generally exhibit the common characteristics of startups, such as agility, innovation, and scalability; while also specializing in finance and technology. (Kijkasiwat, 2021).
Startup valuation
Startup valuation refers to the process of determining the economic value of a start-up company at a specific point in time. Valuation is very important for various stakeholders, including founders, investors, and buyers, because it provides insights about the company's value and potential investment returns (Köhn, 2018).
Research background
Rahimi Klishadi (2017) stated that some startup businesses are only ideas that have very little or even zero income and operational flows. Menon & James (2022) stated that the boom of startups has witnessed the emergence of alternative sources of financing such as venture capitalists, angel investors, etc.
Dhochak et al., (2024) stated that strategic management theories have been used to develop a prediction model based on the artificial neural network technique that predicts the valuation of startups before fundraising.
Hidayat et al., (2022) stated that financial information (revenues) and non-financial information (social media) as well as sectoral and technological differences affect startup stock value.
Hammami et al., (2023) designed a model to evaluate profit predictability in companies active in the financial industry and identified 28 components in this field, in which the company's information environment, analysis of deviations, variability of profit, and analysis of financial leverage have the highest coefficient of importance.
Golshani et al., (2023) by examining the technology valuation strategies of Iranian startups, have identified 7 categories including the development and promotion of the technology valuation discourse, the transformation of existing knowledge in the field of technology into desirable and valuable knowledge, leadership and idea management, comprehensive technology evaluation system, culture creating, regulation in the technology market, and localization of technology valuation.
Research method
The current research is applicable in terms of purpose, descriptive-analytical in nature, and mixed (qualitative-quantitative) in terms of type. In the qualitative part, thematic analysis technique was used, based on interviews with experts and based on the six-step approach of the model (Braun & Clarke, 2006). For sampling, the purposeful sampling method was used, which was based on theoretical saturation. Based on this, a semi-structured interview was conducted with 11 experts. To analyze the findings from the interviews, the method of thematic analysis and qualitative data coding was used in the MAXQDA 2020 software. The validity of the qualitative data was confirmed using the Newman validation method. In the quantitative section, a questionnaire with 199 questions was designed and distributed based on the results of the theme analysis section, which was used for analysis. The content validity of the questionnaire was confirmed by experts, and Cronbach's alpha coefficient was used to check the reliability of the questionnaire, and its value was higher than 0.7. Confirmatory factor analysis was used for construct validity. For confirmatory factor analysis and evaluation of test content from the point of view of structural validity and fit of the research model, structural equation model with partial least squares method was used in SMART-PLS software.
Research findings
The findings of the research included 194 extracted codes in 24 sub-themes and 6 main themes, which in order of importance are business enterprise, environmental factors, technology and innovation, risks, business team, and financial industry.
Conclusion
Research findings show that the most influential issue in startup valuation is "business enterprise". The findings of this research are in line with studies of Suwarni et al., (2020), Passaro et al., (2020), and Lee (2022).
It also highlights "environmental factors" as the second most important dimension in the valuation of startups, which is in line with the research results of Alänge et al., (2022), Kim et al., (2023), and Savin et al., (2023).
On the other hand, it emphasizes the importance of "technology and innovation" as the third dimension, which is in line with the studies of Zorzetti et al., (2022), Koning et al., (2022), and Sibińska (2022).
Research findings highlight "risks" as a fourth dimension. This finding is in line with the studies of Laksmana & Permana (2023), Saravistha & Sancaya (2022), and Oliva et al., (2022).
Research findings emphasize the importance of "business team" as the fifth dimension. This finding is in line with Aryadita et al., (2023), Honoré (2022), and Wise et al., (2022).
The findings of the research show that the "financial industry" dimension has the lowest rank in terms of importance among the dimensions identified in the valuation of startups, and is in line with the studies of Stevy et al., (2023), Berman et al., (2022), and Sreenivasan & Suresh (2024).
According to the results of this research, the following suggestions are presented:
While revenue is an important indicator of financial performance, stakeholders should take a holistic approach to startup evaluation that considers a diverse range of factors beyond revenue generation, including market potential, growth prospects, competitive position, and regulatory compliance. On the other hand, startups should focus on diversifying revenue streams and increasing revenue generation capabilities through innovative business models, strategic partnerships, and value-added services. By offering a set of financial products or services tailored to customer needs and preferences, startups can maximize revenue generation opportunities and strengthen their value proposition in the competitive fintech landscape. Startups must prioritize building scalable and sustainable business models that can adapt to changing market dynamics and regulatory environments while delivering value to customers and stakeholders. By aligning revenue generation strategies with broader business goals and market dynamics, startups can enhance their appeal to investors, increase growth, and achieve long-term success in the financial industry.

Keywords

Startup

valuation

fintech

structural model

innovation

valuation criteria

Subjects

business management

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