Pursuant to the concept of inclusive growth, the authors analyze the transition economies of Central and Eastern European countries, which have become EU members (Bulgaria, Croatia, the Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Romania, Slovakia, and Slovenia). CEE countries characterized by comparable historic and economic backgrounds now seem to reach diversified stages of development. The objective of the study is to identify the level of inclusive growth among CEE countries by taking into account indicators assigned to its seven pillars. The article’s thesis is that CEE countries represent social and economic heterogeneity as well as varied levels of sustainable development. Research methods included the application of the principal components analysis and the multivariate analysis. For a literature review, the bibliometric analysis was conducted with the visualization prepared by the VOSviewer software. The main findings suggest that Estonia, Slovenia, and the Czech Republic seem to exhibit the highest level of inclusive growth while Bulgaria and Romania represent the lowest level of indicators measured.

Research background: People who take non-banking loans are primarily perceived as excluded from accessing bank services. The growth of e-commerce and the increasing digitalisation of customer interactions with banks was particularly accelerated by the COVID-19 pandemic (the first ‘black swan’). These processes have also influenced the rapid growth of the LendTech (LT) sector within FinTech with its digital loans and buy-now-pay-later (BNPL) services. The war in Ukraine (the second ‘black swan’) has led to an energy crisis, increased inflation, interest rates and credit costs, and reduced credit accessibility. In this context, the following research questions are addressed: Are the LT and banking sectors complementary or substitutive in the area of consumer financing? Does complementarity apply to all customer segments and loan amounts? How does the extent of complementarity or substitutability of the LT sector depend on, and to what extent do changes in the regulatory and macroeconomic environment affect, the interaction between the banking and LT sectors? Purpose of the article: The aim of the article is to identify trends in the LT sector within FinTech in the context of assessing the scale and determinants of current and future complementarity of the non-bank sector and the banking sector in the area of consumer credit in time of black swans. An additional purpose of the article is to estimate revenues from the basic operating activities of companies from the on-line channel. Methods: The research process was multi-stage and the research procedure was structured. Due to the lack of a uniform source of data on LT products and services, the study used many data sources — data from the Credit Information Bureau, a primary nationwide survey on LT users a primary survey of people representing LT's managerial staff. The selection of LTs was carried out according to the concept of the monetary sampling unit. The Horvitz-Thompson estimator with Sen‐Yates‐Grundy variance form was used to estimate net operating income for LT from the online channel in 2021. Findings & value added: The LT companies surveyed state that black swans (the COVID-19 pandemic and the war in Ukraine) and the current macroeconomic situation have not significantly affected demand for non-banking loans. The reduction in the opportunities for the LT sector as a result of anti-usury regulations will only lead to a shift in consumer demand to the pawnshop sector and the shadow economy, which will be detrimental to consumers. Complementarity between LT and the banking sector is revealed especially in crisis situations, thus limiting the effects of market shock (limited supply of loans offered by banks). In periods of stabilisation, a rather clear division of preferences is noticeable – in the case of seniors and loans for higher amounts, banks dominate, while in the case of lower amounts and in younger age groups, non-bank institutions are more popular. The mechanism by which shrinking banking services are replaced by LT in short-term crises confirms the importance of LT in balancing the Consumer Finance market in the face of unstable periods. From a medium- and long-term perspective, it should be noted that inflation and rising interest rates will increase the scale of credit exclusion in commercial banks, shifting part of the demand to the non-bank sector. These phenomena have an international dimension. Similar observations were made already in 2012 by the CFPB in the USA and the British FTA, when analysing the consumer finance market immediately after the subprime crisis, emphasising the effects of limiting access to bank consumer loans and the resulting growth of the LT market (Gębski, 2013).

Research background: According to the World Bank (2020), about 60% of adults in developing countries do not use formal financial services. Furthermore, according to the Polish Association of Loan Institutions (2022), about 3 million Poles use loans, most of them obtained online. Among the reasons for more than a decade of growth of interest in the non-bank consumer lending market there are the development of modern technology applications in finance and the establishment of the Lendtech sector. Purpose of the article: The main goal of the paper is to verify the role played by the Lendtech (LT) sector in the consumer credit market in the context of household financial exclusion. The following research questions were asked: Do credit-excluded households take advantage of LT services and, if so, to what extent? What are the behaviours and preferences of those who use consumer credit offered by LT? Do socio-demographic characteristics determine consumer use of loans offered by LT and, if so, what are they? Is the use of loans offered by LT due to credit exclusion or other factors? What action should be taken by participants in the digital consumer loan market interested in its inclusive direction? Methods: The paper uses the following methods: critical analysis of the literature, Kruskal-Wallis test, Mann-Whitney test, and nonparametric regression algorithm: k-nearest neighbors, as well as inductive inference methods. The data used is primary in nature and comes from a nationwide survey, September 2022 (CAWI method) of 1,200 Poles, of whom 200 respondents are Lendtech customers. The quota selection applied made it possible to reflect characteristics corresponding to the population of customers of lending institutions registered in BIK databases. Findings & value added: The article is a pioneering study based on an independent scientific survey, devoted to the Polish LT services market considered in terms of its relationship with one of the types of financial exclusion: credit exclusion. The most important conclusion is that people at risk of credit exclusion find a financing substitute in the LT sector, and thus it plays an important role in reducing financial exclusion, while maintaining the principle of creditworthiness verification.

Referring to the concept of inclusive growth, the authors analyse the transition economies of the Central and Eastern European countries, which are the current EU members (Bulgaria, Croatia, the Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Romania, Slovakia and Slovenia). That region was selected as the CEE countries characterized by comparable historic and economic background but now they seem to reach diversified stages of development. The objective of the study is to identify the level of inclusive growth among the CEE countries, taking into account indicators assigned to its seven pillars. The thesis is that the CEE countries represent socio and economic heterogeneity as well as different levels of sustainable development. The research methods involved the application of the principal components analysis and the multivariate analysis. For literature review, the bibliometric analysis was conducted with the visualization prepared by the VOSviewer software. The main findings suggest that Estonia, Slovenia and the Czech Republic seem to be the ones with the highest inclusive growth. On the other hand, Bulgaria and Romania represent the lowest level of inclusive growth indicators.

Public Employment Services (PES) are identified as important institutions in the process of improving the match between supply and demand in the labor market, which, despite their importance, still do not achieve the desired efficiency. The indicated problem is partly due to the lack of appropriate evaluation methods for the applied labor market policy instruments. This paper aims to verify the possibility of using the two-stage Data Envelopment Analysis (DEA) method in measuring the efficiency of public sector entities. The authors focused on 39 PES operating in Mazovia province, Poland in 2019. In the first stage, the model of technical efficiency of local PES included six variables (four inputs and two outputs). Only seven PES obtained full efficiency. The inefficiency of analyzed PES varied from about 1% to 80%. In the second stage, the attention focuses on the relationship between true unknown efficiency and its determinants (five environmental variables, both demand and supply oriented). Then, the regression coefficients and confidence intervals showed that three out of five variables influence the efficiency results, the share of the long-term unemployed, the share of the unemployed under 30, and the share of the unemployed over 50 in the total number of unemployed.

This study evaluates the scope and consequences of the application of new technologies (NTs) within the Polish banking and insurance sectors and thus contributes to the knowledge of CEE financial market development. The goal is to understand the implementation of particular NTs in two different sectors and identify the motivations, strategies, phases of realisation and cost efficiency depending on the institution’s size. The detail of the study requires the use of qualitative research methods. In-depth interviews are employed to figure out the criteria based on which decisions to implement NTs are made. The findings indicate that the primary objective of NT implementation is to respond to customers’ needs, followed by cost-cutting and achieving more efficient internal processes. The application of artificial intelligence (AI) and machine learning (ML) in risk management areas is still a work in progress. In the next five years cloud computing is expected to become the most important NT and thus will have to meet numerous regulatory requirements.