Purpose – the research aims to find out the main factors that determine the change in the number of FinTech companies in Lithuania and predict the future development of this sector. Research object: FinTech business sector, described as the number of FinTech companies. Research methodology – scientific literature analysis and generalisation, comparative analysis, statistical data collection and systematisation, correlation-regression analysis, scenario method for forecasting. Findings – the main factors that may determine the growth of the number of FinTech companies in Lithuania were identified and several development scenarios of the segment forecasted. The first part analyses related scientific investigations and FinTech's impact on the financial system as a whole. In the empirical part, a correlation and regression analysis of the factors that may determine the change of a number of FinTech companies was performed and ten main factors identified. The possible evolution of the number of FinTech companies until 2024 under 5 scenarios has been predicted. Research limitations – the statistical information used in this research comes from different databases and different sources and may not always be free from certain discrepancies. Practical implications – the obtained results may be of interest for researchers who examine this issue and the Central Bank of Lithuania, performing surveillance of the financial market. The forecast under various scenarios of the economic situation enables the estimation of the impact the FinTech business may have and can be useful for the Ministry of Finance involved in strategic planning. Originality/Value – an attempt was made to fill in the scientific literature gaps and find out what factors influence the most FinTech sector development in Lithuania and how this sector might grow in the future.

The new era of FinTech services enabled the financial sector to benefit from innovative and cost-effective products via process automation, fostering a foundation for more sustainable business growth. Despite considerable research, the determinants of FinTech services adoption by businesses remain mostly unknown. For the first time, a mixed-method study is realized combining the perspectives of FinTech services providers (experts) and FinTech service users (businesses that use FinTech). To elicit the providers’ views, interviews have been conducted with experts from FinTech service providers. From the user side, data generated via online surveys was evaluated in an adjusted Unified Theory of Acceptance and Use of Technology (UTAUT2) model tailored to FinTech specifics using the R implementation of PLS-SEM. The results of this analysis enabled comparisons between the perspectives of providers and users to identify similarities and differences in adoption factors. Correspondingly, conclusions on FinTech adoption encourage FinTech service providers to adjust their solutions to better fit the business requirements. For business owners, they provide valuable insights on how to streamline their financials and foster sustainable growth through efficiency gains.

The paper analyses development and drivers of accelerated growth of peer-to-peer (P2P) lending in Lithuania and its impact on the consumer credit market with a focus on related sustainability issues. Legislative discrepancies between the P2P and banking segments are analysed and their role in predetermining the different development trends within the segments is highlighted. The research is composed of several steps, where each step analyses a certain problem with the aim to compare the processes in both segments, and is using two different approaches based on macroeconomic data and legislative environment analysis. The applied setup of the research allows for distinguishing and quantitative evaluation of the impact on the segments caused by various internal and external factors, such as macroeconomics, technological advantages of P2P platforms, and discrepancies within business regulation. The obtained results could fill in the scientific literature gaps by providing quantitative evidence of the influence the analysed internal and external drivers have on the growth rate of the consumer credit market segments in Lithuania and how this could affect the performance of the whole market, including its sustainability. Conclusions made could be of interest to researchers and practitioners in other countries too, especially those which have similar legislation and regulations within the consumer credit market. Methods used: a scientific literature analysis and generalisation, comparative analysis, statistical data analysis, correlation–regression analysis, mathematical modelling.

This study aims to develop an original financial intelligence quotient (FIQ) measurement conceptual model, including guidelines for adequately handling personal finances in four developed areas to serve as benchmarks of financial intelligence. Four hypotheses were raised, one of them consists of four parts. Methods used: a questionnaire to determine how well a person’s financial decisions comply with financial behaviour guidelines, Cronbach’s Alpha coefficient to determine the internal consistency of the scales used in the questionnaire, Spearman correlation coefficient to determine the linear dependence between the variables, a linear regression model was developed to substantiate the hypothesis, the MannWhitney-Wilcoxon rank-sum criterion, the KolmogorovSmirnov test to choose the data distribution according to the normal distribution, descriptive statistics, the Kruskal-Wallis test to support the hypothesis. The results show that an individual’s FIQ influences financial decision-making in essential areas of personal finance management and varies due to education but is not dependent on gender and age. Research limitations: The study focuses only on FI and its impact on the economic well-being of Lithuanian students; the study uses oneyear data; data sets for different age groups were not the same size; and the data was not distributed in groups according to the normal distribution. Keyword : financial intelligence, financial intelligence quotient (FIQ), financial literacy, financial well-being, financial behaviour, personal finance

This study analyzes the development and determinants of control premiums in mergers and acquisitions in the European market from 2009 to 2022 (i.e., stock volatility, liquidity via money supply, sectoral growth, transaction volume, market capitalization, free cash flows, presence of a toehold, public listing, cross-border transactions, payment types, and sectoral relatedness), whereby control premiums represent the premium that buyers pay above the current market value of a company to gain control. The empirical analysis implements linear as well as quantile regression analyses. Results reveal that the average and median premiums fluctuated notably between 2009 and 2022, with the lowest premiums paid in 2009 and the highest in 2022. Factors such as the volatility of the stock market, capital liquidity, and deal activity within certain sectors have a consistently significant influence on the level of premiums if a longer period of analysis is selected. Cross-border status, payment structure, stock market listing of the acquiring company, and the build-up of a toehold influence the premiums paid in shorter- and longer-term analyses. In contrast, neither the market capitalization nor the free cash flow of the target company has a significant influence on the premiums paid.

Purpose – to analyse the main borrowing alternatives available to Lithuanian households and the credit market as a whole, focusing on its peer-to-peer (P2P) segment, the forecast of its growth, and possible challenges. Research methodology – the research methods applied were scientific literature analysis, statistical data analysis, comparative analysis, correlation-regression analysis, linear trend forecasting method. Findings – the prevailing borrowing alternative for Lithuanian households still remain bank credits. Besides, borrowing from P2P market is becoming more and more popular. Although the macroeconomic environment for all the credit market segments is the same, the P2P segment is developing significantly faster. If this trend remains unchanged, the whole credit market is likely to face challenges, such as the growth of overdue loans, insolvent customers, the rising share of non-performing-loans (NPL), etc., that may affect its overall stability. Research limitations – the empirical study relies on the country’s macroeconomic indicators that influence household borrowing. Such factors as borrower’s age, income level, marital status and others were not taken into account in this study. The forecast of the P2P segment growth of the consumer credit market and comparison with its banking segment is based on the analysis of 4 years of real monthly statistics for both segments. Practical implications – the performed analysis and its results can be useful for the future research within the household borrowing trends, especially in Peer-to-Peer platforms, and specifically for the Central Bank, the Ministry of Finance and other institutions that regulate the credit market, as it provides information on modern borrowing trends and the challenges it might bring. Also, for P2P platforms themselves, planning and further developing their activities and adjusting lending conditions with the aim to attract higher-quality customers. Originality/Value – household borrowing, the credit market and the P2P platforms are widely analysed by both academics and financial institutions, such as central banks. However, it is mainly limited to the analysis of statistical data and does not pay attention to possible market development issues. This study focuses on the analysis of the growth trends of the P2P market and the potential challenges that may arise thereafter. Keyword : household borrowing, modern borrowing trends, credit market, commercial banks, P2P segment, overdue loans, non-performing loans