Economic and technological determinants of newstartups in the global financial technology sector

The quality and diversity of financial services offered by the development of today's financial technologies is increasing over time. In this development, the share of financial technology ecosystem is quite large. FinTech concept, which is formed by combining financial and technology words, eliminates the traditional financial service concept by using innovative technologies such as internet, mobile, data analytics, and facilitates the access of financial services to consumers with an innovative approach. FinTech startups are companies that benefit from the opportunities created by new technologies to provide innovative and high quality financial services, products and business models for both consumers and enterprises. There are different business models where FinTech startups operate. These business models are payments, asset management, crowd funding, lending, capital market and insurance services respectively. Fintech startups compete directly with traditional banking and financial institutions and, in many ways, surprise banks and financial institutions. FinTech startups provide innovative financial products, services and business models to consumers by using artificial intelligence, machine learning, application programming interfaces (API), blockchain and quantum information technologies. Depending on emerging technologies, FinTech startups continue to change how financial services should be offered. The benefits of FinTech startups to consumers are not only customer experience, speed and convenience, but also low costs and access to financial services at anytime and anyplace. In this thesis, economic and technological determinants which cause FinTech startups in global financial technology sector were examined with the help of count data model methods. The variables considered to have a direct and indirect effect on the emergence of FinTech startups; economy, banking and finance, entrepreneurship, innovation and academic fields. The study consists of 490 observations of 49 countries using the annual data for the period 2007-2016. Constructed panel data has been used in research. Correlation matrix and variance inflation factor (VIF) values were examined for high correlation and linear relationship between independent variables in the study. Negative Binomial Regression Model was used because of dependent variable counting data and overdispersion. The values of the independent variables with one year delay were included in the research model. Due to the fact that 47% of FinTech initiatives were established in the USA, research results were examined including and excluded from US FinTech startup data. It is determined that US FinTech data affects the results of the research. The research model has been run separately with economic, technological and all independent variables. According to the results obtained in the model where all the independent variables are run; The increase in unemployment rate is observed in economies, we see FinTech startups more often. In the study, it has been realized that the increase in the number of scientific and technical journal articles of the countries has a positive effect on the number of FinTech startups. The rise in innovation, one of the technological determinant, has been found to lead to more FinTech startups. It was determined that the improvement in financial markets and increase in productivity of the labor market leads to an increase in the number of FinTech startups.