Fintech in the eyes of Millennials and Generation Z (the financial behavior and Fintech perception)

The rise of robo-advisor wealth management services, which constitute a key element of fintech revolution, unveils the question whether they can dominate human-based advice, namely how to address the client’s behavioral biases in an automated way. One approach to it would be the application of machine learning tools during client profiling. However, trained neural network is often considered as a black box, which may raise concerns from the customers and regulators in terms of model validity, transparency, and related risks. In order to address these issues and shed more light on how neurons work, especially to figure out how they perform computation at intermediate layers, this paper visualizes and estimates the neurons’ sensitivity to different input parameters. Before it, the comprehensive review of the most popular optimization algorithms is presented and based on them respective data set is generated to train convolutional neural network. It was found that selected hidden units to some extent are not only specializing in the reaction to such features as, for example, risk, return or risk-aversion level but also they are learning more complex concepts like Sharpe ratio. These findings should help to understand robo-advisor mechanics deeper, which finally will provide more room to improve and significantly innovate the automated wealth management process and make it more transparent.

The analysis of the financial technologies introduction has proved that their application over-complicates the institutional structure of the global financial system. As a result, usual functional relationships cease to operate, new institutes and interdependencies appear, and systemic risks increase. In this context, the system instability increases, resulting in a transition to a new institutional status. The analysis of the financial technologies impact on the stability of financial system shows that the lack of institutional support for new financial technologies is the most important catalyst for the financial industry destabilization and the formation of financial bubbles in various market segments.
The ways to reduce the negative impact of financial technologies on the financial system stability (such as development of international prudential standards; revision of the licensing regime for financial companies; “regulatory sandboxes”, which test new technologies, business models and algorithms underlying the Fintech innovations; legal regulation of ownership of digital tokens; and clear definition of the blockchain technology in various areas of life, etc.) have been proposed.

FinTech startups and services are one of the most dynamic segments of the modern economy. New financial technologies have already attracted many investors and form millions of budgets. Changing the traditional financial services concept, FinTech companies formed a new niche within the financial services market, the dynamic development of which determines the relevance of the development and implementation of an effective regulatory and oversight system.
The purpose of the article is to develop an economic and mathematical model for forecasting the development of the FinTech market on the example of Ukraine. In order to study the development of the FinTech industry, a multiple regression model was presented. The model describes the dependence of the total investment value of FinTech from venture investments in financial technology, venture investments in other technologies and venture investments in online lending. Based on this model, the effect of attracting investments with new FinTech projects on the total volume of investments in the industry was clarified. According to the model, with a change in investments in FinTech by 1%, the total rate of venture investments decreases by 0.03, funds in new projects of other companies grow by 0.05, and venture investments in online lending increase by 0.89. According to the analysis of regulatory legislation in the foreign countries of the FinTech services sphere, it was found that the regulation of most of the risks associated with the development of FinTech services falls within the competence of different supervisory authorities, requiring cross-sectoral cooperation between public institutions.