The process of digitalization in the education sphere is the new paradigm and model of high technologies development. The importance of the digital delivery of financial education is growing in parallel with the digitalisation of our societies and economies. Digitalization of education assumes to include two inseparable components – a) classroom learning concepts and b) online learning methods. It is now more important than ever to make sure that the innovative use of digital technologies in the field of financial education effectively contributes to increasing financial resilience and well-being, and that governments design and implement effective digital financial education initiatives. The purpose of this article is to present the impact of digitalization on higher financial education, the challenges facing students and teachers in these process and to analyse the level of digital financial culture. Emphasis is placed on the practical application of the digitalization process in the teaching of financial disciplines in universities.

ERP systems significantly optimize many business processes and activities, but often their implementation and use in companies is a risky endeavor. They are the subject of various scientific studies and analyses in the fields of business, accounting and finance. The main focus in them falls on the process of implementing these systems, while the subsequent stages, risk analysis and long-term strategy are less affected. On this basis, this research paper proposes a methodology for quantitative assessment of identified ERP risks. It is based on a five-level matrix measuring three risk factors—influence, impact and vulnerability. The methodology has been empirically tested in three companies, different in size and operating in different economic sectors. The results show that the level of risk depends not only on the scale and complexity of the business, but also on the degree of integration of ERP solutions. Periodic application of the risk assessment methodology helps identify problem areas and facilitates management decision-making.

The purpose of this paper is to analyse and systematize the key challenges to understand the role of digital economy and the relationship with financial risk management. The author put forward the provision on the valuation and measurement of financial risk in contexts of digital economy in Bulgaria. The paper mainly aims to examine the influence of digital finance on enterprise financial risk and its mechanism. The results of the study are presented in Figure 2. Moreover, it attempts to analyze whether digital finance corrects the distortion of traditional financial elements and whether it can effectively improve enterprise financial risk and further verify the inclusion and transmission mechanism of digital finance.

This study presents a novel method for approximating inequality by converting expert qualitative data from 32 EATLP country reports into quantitative indicators with the help of large language models (LLMs). Nine sub-indicators—covering aspects such as economic rights, judicial enforcement, tax policy, and anti-discrimination—are aggregated to build an overall indicator. Validation against the World Inequality Database's Gini coefficients shows that the composite index explains more than half of the variation in post-tax Gini, validating the role of legal and institutional factors in shaping inequality outcomes. A sub-index based solely on tax-specific metrics, the Tax Equality Score, also displays a positive association with Gini differentials before and after taxation. While it suffers from some limitations, such as potential model biases and no temporal dimension, this approach shows the potential of LLMs to supplement traditional socioeconomic data. It offers a scalable and cost-effective way to capture complex policy and institutional dimensions of inequality.

In 1952, Harry Markowitz established the foundations of Modern Portfolio Theory by introducing a mean–variance framework for constructing investment portfolios that optimize the trade-off between risk and expected return. Expanding upon this classical framework, this paper develops an analytical algorithm to determine optimal asset weights for long-only portfolios that minimize total risk. We derive the necessary and sufficient conditions through rigorous determinant-based identities, providing a closed-form solution for achieving the global minimum variance. The theoretical findings are demonstrated through three numerical examples: the first examines a standard six-asset portfolio using an admissible covariance matrix; the second serves as an algebraic cautionary case by identifying negative variance when the input matrix fails to satisfy the criteria for positive definiteness; and the third example validates the practical application of the proposed identities using empirical market data.

An integrated framework is developed for classifying and measuring financial assets, recognising expected credit losses (ECL), and disclosing financial risk in non-financial entities. Its design is based on the requirements of International Financial Reporting Standard 9 Financial Instruments (IFRS 9) and International Financial Reporting Standard 7 Financial Instruments: Disclosures (IFRS 7). The framework links contractual cash-flow characteristics, business models, measurement categories, impairment approaches, and risk disclosures in a single sequential procedure. Its applicability is examined using publicly available 2024 annual reports of ten large non-financial corporations from multiple sectors. A ten-indicator index is constructed to assess public traceability between accounting policies, loss allowances, trade-receivable information, forward-looking assumptions, and credit-risk disclosures. The application yields an average integration score of 94.00%, with stronger reporting for financial-asset categories, accounting policies, trade receivables, and the general or simplified ECL approach. More limited traceability is observed for the methods used to incorporate forward-looking information and for detailed provision-matrix disclosures. The framework is intended as a structured procedure for analysing public financial statements when internal credit-risk databases and model inputs are unavailable. Its contribution lies in integrating classification, subsequent measurement, impairment, and disclosure rather than treating them as separate compliance tasks. The proposed sequence can support accounting policy design, audit documentation, and comparative disclosure analysis. The index should be interpreted as a measure of reporting traceability rather than the economic accuracy of entities’ internal credit-risk estimates.