FINTECH COMPANIES: INNOVATION, ALGORITHMS AND CUSTOMER CENTRIC PERSPECTIVE - A cross-sectional study on algorithmic trading in the Fintech industry
In the last years the financial sector has been subject to many changes, in particular since 2008 financial crisis many customers started to appreciate new digital financial companies, instead of traditional ones, that offer innovative solutions for financial services. In fact they are able to offer more effective, efficient and less expensive services than traditional institutions. However, their innovativeness doesn’t consist only in a simple product or process innovation but they are characterized by a total innovation in terms of business model; they focused on particular elements that allow to get competitive advantage. A particular importance has to be given to leverage on technology as one of the main elements at the base of Fintech companies. Particularly interesting under this point of view are trading algorithmic trading fintech companies, in which algorithmic trading systems are a fundamental element to run their business and without it the business could not exist. The purpose of this thesis work was to analyse the impact of algorithms in the Fintech industry, in particular on what concerns automatic investments by trading algorithms, and how they are able to take better and faster decisions than humans can do allowing people to invest in a less demanding and more secure and profitable way. For this study the author has decided to use a cross-sectional design, interviewing respondents from companies and experts. All interviews have been a semi-structured form and have been done in 2021. The research evidenced many aspect about algorithms for trading in particular about their development, the automatization of trading activity and future expectations for the future. The analysis of findings showed many important concepts: the great efficiency that characterized algorithm’s use, the fundamental importance of the research process in the algorithm’s development and the emotional aspect linked to algorithmic trading.
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