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For more than a decade, the Financial Technology (FinTech) industry has been growing, and it has reshaped how payments were made and brought new financial service products to the market. FinTech has created innovative disruptions to traditional, long-established financial institutions (e.g., banks and investment firms) in financial services markets. The worldwide blooming of FinTech has caused universities around the globe to teach their students (particularly those in the IT and finance disciplines) about practical and contemporary knowledge on FinTech. This paper discusses our recent survey study to investigate the status quo of offering FinTech education and training by Australian universities. Our study involved two rounds of online data collection (one in November 2021 and the other one in June 2022) from 41 sample universities in Australia. Among our various findings, we observed that, although Australian universities are increasingly aware of the importance of and the demand for FinTech studies, FinTech has still not yet become a mainstream study discipline. This observation indicates that, in Australia, FinTech studies have generally gone through the inception stage and entered the growth stage.

Purpose: Set within the context of International Financial Services (IFS), this research aims to considers the demographic profile of IFS apprenticeship candidates in relation to gender equality and social mobility in Ireland. This study also offers valuable insights as to the gendered nature of these "new" apprenticeships and examine whether these programmes provide opportunities for social mobility. Design/methodology/approach: Implementing a quantitative approach, underpinned by a positivist stance, this study analyses Irish national apprenticeship data relating to IFS programmes (n = 1118). Non-parametric tests were applied in the analysis of the gender dimension, while to analyse social mobility, the socio-economic status and spatial profile of candidates were compiled and analysed using the Pobal HP Deprivation Index (SA). Findings: The findings revealed more women are undertaking non-traditional apprenticeship programmes as compared with traditional craft apprenticeships. Within the IFS context, while female participation was seen to be growing, gender divergence was observed in terms of programme level, with a greater number of men, as compared with women, engaging in higher-level degree apprenticeship programmes. The findings also show that IFS apprentices are primarily from socio-economic areas that are above average. This trend indicates a distinctive candidate who is more aligned with the sectoral profile of IFS than that of traditional apprenticeship programmes. Such findings reveal that the "widening participation" aim of IFS apprenticeships is not yet fully realised with issues of gender inequality and social mobility persistent within the wider IFS sector. Originality/value: This study provides an important dimension to both academic and practitioner literature concerning apprenticeships. To date, there has been a proliferation of publications concerning the beneficial impact of skills and vocational-led apprenticeships. However, limited attention has been directed to non-traditional apprenticeships and even less still within the setting of IFS. This research initiates the process of addressing that gap within an Irish context. This study also adds to the existing apprenticeship discourse regarding issues of gender and social mobility by examining the gendered nature of IFS apprenticeships and well as assessing whether these apprenticeships aid social mobility.

We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial institution to financial institution. In this study, we create a machine learning prediction model using items and added items that are based on the current customer grade of our bank,- and the purpose is an optimal model that considers the adequacy of existing variables and the validity of additional variables through comparison between models. Using Lasso, Elastic net and Multinomial Logistic Regression, Decision Tree, Random Forest, and Support Vector Machine, we propose that the best model be found and gradually applied to customer grade calculation criteria.

In private law, fiduciary duties are in general linked to fiduciary relationships, i.e., when a fiduciary relationship exists, the parties are deemed to have corresponding fiduciary duties. However, this study shows that fiduciary relationships and fiduciary duties should not always be equated. This article seeks, first of all, to shed light on the interplay between fiduciary duties and fiduciary relationships, as well as to clarify which particular duties can be considered fiduciary. The authors then seek to reveal the specific cases in which fiduciary duties arise and explain their content to ensure the sustainability in these relationships governed by private law. Thereby, a conclusion is made that certain subjects of fiduciary relationships, such as, for example, the manager of the company, the bank and the trustee, have fiduciary duties, but this is not the case for, as an example, the insurer and the doctor.

The default risk, one of the main risk factors for bonds, should be measured and reflected in the bond yield. Particularly, in the case of financial companies that treat bonds as a major product, failure to properly identify and filter customers' workout status adversely affects returns. This study proposes a two-stage classification algorithm for workout prediction based on the history data of individual customers such as transaction details of financial companies secured after loans, which is collected over 10 years. The first stage is to rank variables that are closely related to the workout application based on feature selection. In the second step, the first to nth cumulative variables input to each machine learning method generate n candidate classifiers, respectively. Among the total candidates, the model with the highest classification accuracy was selected as the optimal one, which is the Gradient Boost combined with F-score-based feature selection.

It is meaningful to create a comprehensive score to extract information from mass continuous data when they measure the same latent concept. Therefore, this study adopts the logic of psychometrics to conduct scales on continuous data under the Rasch models. This study also explores the effect of different data discretization methods on scale development by using financial profitability ratios as a demonstration. Results show that retaining more categories can benefit Rasch modeling because it can better inform the models. The dynamic clustering algorithm, k-median is a better method for extracting characteristic patterns of the continuous data and preparing the data for the Rasch model. This study illustrates that there is no one-way good discretization method for continuous data under the Rasch models. It is more reasonable to use the traditional algorithms if each continuous data variable has target benchmark(s), whereas the k-median clustering algorithm achieves good modeling results when benchmark information is lacking.

This article outlines a novel approach for career readiness which embeds a global engagement trip within a social entrepreneurship course. Utilizing an empathy driven approach, the instructional innovation exposes students to social impact and innovation in an entrepreneurial setting, provides an opportunity for rich engagements with social and micro-entrepreneurs, and facilitates connection with self and others. Reflexive assignments and dialogues are integrated throughout the instructional innovation allowing students to identify and reflect on their aspirations and intentions for creating societal impact in their career journeys. Participation in this experience has resulted in outcomes related to career goals, including new plans for building social impact into work and renewed social entrepreneurial intentions. Instructions, exercises, and evidence of their effectiveness are provided.

Three field studies and a laboratory experiment reveal racial discrimination in financial loan services. The results show that (1) service employees provide Black (vs. White) customers with inferior service outcomes (i.e., products offered), (2) Black (vs. White) customers experience inferior service processes (employees' warmth/competence), and (3) Black (vs. White) customers report lower loyalty intentions toward the firm. Such discrimination is not only morally wrong and illegal; it is also bad for business. Therefore, the authors also show when and why racial discrimination is mitigated: namely, when Black customers signal higher socioeconomic status, or a Black customer's company (for which they seek the loan) has a more complex and sophisticated legal structure (corporation vs. sole proprietorship). Exploring this mitigation effect further, the authors show that a more sophisticated business structure increases the employee's trust toward Black customers, which reduces the perceived default likelihood and increases the likelihood to offer a loan; yet, this process does not emerge for White applicants. The findings point to managerial and policy implications to mitigate racial discrimination. [ABSTRACT FROM AUTHOR]

Researchers and practitioners in financial services utilize a wide range of empirical techniques to assess risk and value. In cases where known performance is used to predict future performance of a new asset, the risk of bias is present when samples are uncontrolled by the analyst. Propensity score matching is a statistical methodology commonly used in medical and social science research to address issues related to experimental design when random assignment of cases is not possible. This common method has been almost absent from financial risk modeling and portfolio underwriting, primarily due to the different objectives for this sector relative to medicine and social sciences. In this application note, we demonstrate how propensity score matching can be considered as a practical tool to inform portfolio underwriting outside of experimental design. Using a portfolio of distressed consumer credit accounts, we demonstrate that propensity score matching can be used to predict both account-level and portfolio-level risk and argue that propensity score matching should be included in the methodological toolbox of researchers and practitioners engaged in risk modeling and valuation activities of portfolios of consumer assets, particularly in contexts with limited observations, a large number of potential modeling features, or highly imbalanced covariates. [ABSTRACT FROM AUTHOR]

The financial services industry has undergone a massive transformation in the contemporary disruptive, volatile, uncertain digital age. The study aimed To discuss the role of customer satisfaction and experience in financial services marketing in the digital world, To provide a glimpse of cyber security aspects in financial services, To give an overview of the concept of sustainable finance, To discuss the emerging sustainability aspects evolving in the finance industry and To present a summary of industry-specific initiatives to promote sustainability. The data has been collected as review papers and shown When it comes to financial services marketing in the digital world, the conversion of traditional marketing to digital marketing has forced the banks and financial services players to perceive the relative importance of customer experience to sustain in a highly disruptive, transformational, and competitive digital era. Earning customer trust and loyalty by addressing security and sustainability issues and adapting to the latest technologies is the prime focus for key financial service players. The traditional product-centric marketing strategy is outdated; the focus is now on a customer-focused marketing strategy. The current paper provides an overview of the financial services industry in the digital era, including the opportunities, challenges, and recent trends in the industry. The result emerging cyber security threats, sustainability risks, and related aspects of the financial services industry are highlighted. Significant sustainability risks faced by the finance sector in contemporary times and the industrial initiatives to promote sustainability in the finance industry have been discussed. The relevance of the "sustainable finance" theme in a digitalized world is highlighted. The importance of sustainability assurance reporting is concerned. [ABSTRACT FROM AUTHOR]

The paper conducts a comprehensive review based on the topic of experience in financial services. The paper presents the evolution and structure on the topic. A bibliometric analysis of literature is performed around the key components using Bibliometrix of R package and VOSviewer. The analysis is based on 137 articles, which are published in 73 leading journals between the years 1985 to 2021. Using the dimensions database, research articles on experience in financial services are extracted and analysed to uncover this topic's intellectual development and key themes through a mixed-methods approach of quantitative bibliometric and qualitative content analyses. More specifically, descriptive statistics, Lotka's law, co-occurrence networks, thematic maps, and bibliometric coupling are used for the analysis. The bibliometric analysis facilitates technical examination and visualization of the scholarly financial service experience research. Based on grounded theory, content analysis is successively conducted to establish theoretical building blocks of financial service experience, providing a conceptual model of this concept. Using bibliometric coupling, nine significant clusters are identified: experience and related constructs, experience in the digital and social media era, experience and quality, experience and customer journey, brand and digital financial services experience, experience and financial institutions, experience and employees, experience and financial literacy, and customer experience management. The study employs more updated and relevant analysis techniques and provides a critical review of the topic. The bibliometric analysis enabled scientific investigation and visualization of the scholarly financial services experience literature providing a holistic understanding of the concept, illustrated topic's scholarly evolution, and revealed key directions for future research. [ABSTRACT FROM AUTHOR]

The article examines the supervision of the activities of non-banking financial institutions based on current legislation. The object of the study is the set of relationships that arise in the process of financial control over the activities of non-banking financial institutions. The subject is the laws and regulations of the National Bank of Ukraine regulating the activities of non-banking financial institutions. The methodological basis of the research is general scientific and private scientific methods of cognition. It is noted that effective control and supervision of the activities of non-banking financial institutions is an integral condition for ensuring the stability and development of the financial market, protecting the rights and legitimate interests of consumers of financial services. Supervision of non-banking financial institutions is characterized by the use of: a risk-oriented approach, which assumes that supervisory measures are carried out with different frequency, intensity and concentration on the identified risks of a non-banking financial institution depending on its risk profile. Risk-based supervision arises as a supplement to formal compliance supervision. Supervision of the activities of non-banking financial institutions includes: macro prudential supervision aimed at ensuring the safety and stability of the financial market; oversight of the judgment-based regulatory model; proportional (selective) regulation and supervision; behavioral supervision; a combination of forms of supervision based on a balanced combination of various forms of control and supervision activities of the National Bank of Ukraine. Expanding the powers of non-banking financial institutions to combine types of activities will lead to the development of the market by reducing the costs of its participants and introducing new digital technologies into the practice of non-banking financial institutions. One of the most urgent tasks facing the National Bank of Ukraine today is to overcome the approach to regulation exclusively by types of legal entities by moving to a more progressive model of regulation by types of activity. [ABSTRACT FROM AUTHOR]

Deep neural network (DNN) architectures such as recurrent neural networks and transformers display outstanding performance in modeling sequential unstructured data. However, little is known about their merit to model customer churn with time-varying data. The paper provides a comprehensive evaluation of the ability of recurrent neural networks and transformers for customer churn prediction (CCP) using time-varying behavioral features in the form of recency, frequency, and monetary value (RFM). RFM variables are the backbone of CCP and, more generally, customer behavior forecasting. We examine alternative strategies for integrating time-varying and non-variant customer features in one network architecture. In this scope, we also assess hybrid approaches that incorporate the outputs of DNNs in conventional CCP models. Using a comprehensive panel data set from a large financial services company, we find recurrent neural networks to outperform transformer architectures when focusing on time-varying RFM features. This finding is confirmed when time-invariant customer features are included, independent of the specific form of feature integration. Finally, we find no statistical evidence that hybrid approaches (based on regularized logistic regression and extreme gradient boosting) improve predictive performance—highlighting that DNNs and especially recurrent neural networks are suitable standalone classifiers for CCP using time-varying RFM measures. [ABSTRACT FROM AUTHOR]

Financial technology (Fintech) has influenced business by helping create better services for consumers and businesses. Fintech, however, brings new challenges for regulators, who struggle to keep pace with the constant evolution of technology and the resulting disruption. The progress of technology and regulations in the Fintech industry has been uneven across developed and developing countries, resulting in numerous opportunities and challenges. Considerable progress has recently been made in the adoption of Fintech and the subsequent development and implementation of regulations in the US, the UK, and India. While the United States (US) and the United Kingdom (UK) are global leaders in Fintech innovation, India has shown fast-paced growth in adopting and utilizing Fintech services. This paper examines the growth and evolution of Fintech in the US, the UK, and India and also explores how the regulatory agencies across these countries have responded to the evolution of Fintech. This paper finds that economies should work towards improving digital infrastructure, financial inclusion, and financial literacy and enhance the collaboration among regulators, Fintech firms, and other stakeholders. [ABSTRACT FROM AUTHOR]

Australians are embracing new forms of digital finance products and services, which includes purchasing cryptocurrencies and non‐fungible tokens (NFTs). There has been an increase in investment scams associated with cryptocurrencies. In this article, we sought to understand from cryptocurrency and NFT investors, who is vulnerable and what vulnerabilities exist. We surveyed 745 Australians aged 18 and over who have purchased cryptocurrencies or NFTs. We used sociological perspectives of consumer vulnerability that focus on internal and external factors to analyse our findings. We found that both socioeconomic advantaged and disadvantaged Australians are vulnerable. The vulnerabilities include concerns over security, unsolicited advice, limited options for learning, and insufficient financial and IT literacy. The findings suggest that online financial education is needed from trusted independent sources to help combat scams and to keep Australians and their crypto assets safe. We recommend that more opportunities to educate individuals about alternative forms of financial products are offered in compulsory, vocational and higher education settings. [ABSTRACT FROM AUTHOR]

Switzerland and the UK recently signed the Berne Financial Services Agreement on Mutual Recognition of Financial Services. This agreement addresses the mutual recognition of the equivalence of the respective legal and supervisoryframeworks in selected areas of the financial sector, with the goal of strengthening competitiveness, promoting cooperation and enabling and facilitating cross-border market access of the two countries. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has transformed the needs of consumers of goods and services. As a result, there was an increase in the volume of BigTech activity. At the same time, BigTech took into account the expectations of consumers in obtaining complementary services. This led to the growth of BigTech's offerings of financial services to its clients. The purpose of the article is to clarify the place of financial services in the BigTech ecosystem and to identify the priority areas of activation of the provision of financial services by BigTech firms. The article describes the BigTech ecosystem from an institutional point of view. The study presents the composition of participants of the BigTech ecosystem, which are connected by a digital platform and the use of information technologies that contribute to the sale of goods and the provision of services, including financial ones. The technical, economic, legal, and marketing prerequisites for providing BigTech financial services have been identified. This made it possible to substantiate the influence of consumer needs on the formation of the policy of providing BigTech financial services. It has been confirmed that BigTech implements a policy of providing financial services that meet customer expectations. The weaknesses and strengths of BigTech financial services are identified. The threats and opportunities of providing BigTech financial services are substantiated. The conducted research made it possible to formulate geographical, product, and client directions for the development of the provision of BigTech financial services. [ABSTRACT FROM AUTHOR]

We discuss the geoeconomics of the Single Market in financial services in the European Union (EU). We examine three case studies that concern the EU and other major jurisdictions and that range from incipient geoeconomic use to outward weaponisation of the Single Market in finance. These cases are (1) the post‐2008 crisis transatlantic tug of war, whereby the EU leveraged its Single Market vis‐à‐vis the United States, seeking to set the rules for global finance; (2) the Brexit negotiations, when the EU acted as a bloc against the United Kingdom and successfully safeguarded the integrity of the Single Market; and (3) the fulsome war in Ukraine, during which the EU 'weaponised' its Single Market through the adoption of financial sanctions against Russia. We argue that a combination of external and internal factors accounts for this pattern: the evolution of the international economic and political system, in particular, the increasing challenges to the liberal international order, and intra‐EU developments, namely, the EU's ability to deploy its Single Market geoeconomically. [ABSTRACT FROM AUTHOR]

The use of digital technology in finance has led to the creation of more efficient and convenient financial services at lower costs, providing customers with a more attractive experience than traditional financial services. This trend has become dominant in recent decades, but it is a relatively new field in Vietnam. Vietnam has great potential for financial technology (hereafter referred to as fintech) development: the young population is increasingly using digital technologies in their daily lives, and the country has a relatively developed telecommunications and e-commerce infrastructure. However, fintech in Vietnam also faces many challenges, such as information technology risks, increased competition in the financial institution market, and difficulties in non-banking organizations management and supervision. Coordination among government agencies, fintech businesses and citizens is needed to address these challenges. The government needs to improve legal policy, raise public awareness, and create favorable conditions for fintech development. Fintech companies need to improve their products and services quality to meet people’s needs. The population needs to be aware of financial technologies to be able to effectively use fintech products and services.

The concept of „automated decision making” (ADM) is currently a key vector reshaping industries in the era of technology-based decision making, and the use of artificial intelligence (AI) in this process is a hot topic worldwide with the adoption of generative AI tools like ChatGPT. ADM enables companies to use technology for tasks that were not long ago the domain of human judgment. AI is essential in financial services, such as credit worthiness assessment, automated investment advice (often called robo-advice) or insurance. The regulation of activities related to ADM is contained in various acts and regulations, including the Sale of Goods Directive 2019/771, the Digital Contracts Directives 2019/770 and the EU General Regulation on Data Protection. However, these directives do not contain special rules for new technologies such as Artificial Intelligence (AI). Although recently, the EU has moved forward with regulations on product liability laws affecting digital products and services, with the EU Data Act, the EU Cyber Resilience Act and the highly publicized EU AI Act - regulations with a transition period of two years for compliance, the speed with which in practice the ADM tools are developed and trained make the legislative efforts slow and incomprehensible. In light of this issue, this article explores the relationship between AI, ADM and discusses whether existing EU consumer law is equipped to deal with situations where AI systems are either used for internal purposes by companies or offered to consumers as the main subject of the contract. The paper will reveal a number of gaps in current EU consumer law and briefly discuss future legislation. This article also reviews the efficiency of key EU consumer law directives for the conclusion of contracts with consumers through the use of AI, with recommendations for clarifications and additions to improve the use of ADM.

Accounting and the entire financial field are among the fields with an extreme degree of exposure to human error. Although there are procedures to limit these errors, the accountant is subjected every day to unforeseen situations. These challenges value his expertise and capabilities, but, very often, rather his endurance and patience are put to the test, as there is an overwhelming number of tasks that could ideally be automated, limiting the range of errors. Artificial intelligence, already used in various fields, has an undoubted potential to streamline the processes of data extraction, expense prediction, and customer flow management synchronously. On the other hand, by paying more attention to the branch of artificial intelligence in the financial field, it is natural that data security will be improved, behavior forced by the fact that we will have to store and handle huge amounts of confidential data, and cyber security will not be a choice or a higher level, but a necessity.