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.

The primary aim of this study is to delve into the factors influencing individuals’ readiness to embrace financial technology (FinTech) services in Bangladesh. Specifically, the study focused on Bangladeshi fintech consumer’s knowledge about contemporary digital financial tools, such as mobile-based payment service apps. Data collection was carried out using a survey questionnaire tailored to the Bangladeshi context. Participants were invited to participate in the survey, and their responses were gathered upon their consent. A five-point Likert scale, ranging from ‘1’ for ‘Strongly Disagree’ to ‘5’ for ‘Strongly Agree,’ was employed to gauge the questionnaire items. The final sample size was 450 respondents. To assess the hypotheses, a 5% significance level was employed, with data analysis conducted using SPSS software. The findings underscore a positive and statistically significant impact of financial literacy, digital literacy, and financial self-efficacy on the adoption of FinTech services in Bangladesh. Collectively, these variables elucidate 48.20% of the variance (R2=0.482) in predicting individuals’ adoption behavior of FinTech. Financial self-efficacy (β = 0.574; t-value = 8.394) has the highest effect on FinTech adoption compared to the other two factors. Additionally, a substantial correlation coefficient (r=0.634) is present between digital literacy and FinTech adoption. This study contributes to the extant literature on FinTech services by providing valuable insights that enhance scholars’ understanding of the emerging financial technologies’ significance and their predominant impacts within the Bangladeshi FinTech ecosystem. These findings hold implications for policymakers, financial institutions, and stakeholders seeking to promote FinTech adoption and foster financial inclusion in Bangladesh.