Riscurile financiare și impactul acestora asupra raportărilor financiare în contextul tehnologiilor de ma-chine learning

Abstract

In a European economic environment characterized by high volatility, financial uncertainty, and increasing demands for accounting transparency, the use of modern analytical tools to manage financial risks has become essential. This research explores how machine learning technologies can enhance the identification, assessment, and reporting of financial risks while increasing the credibility of accounting information. The study pursues two main objectives: (O1) to define and conceptualize financial risks and their impact on accounting reporting, and (O2) to explore machine learning as an emerging tool for predicting financial imbalances. The research methodology is based on a bibliometric analysis of the specialized literature using databases such as Web of Science, aiming to identify the main trends, authors, and research clusters in the field. The network of keywords related to financial risk management techniques was analyzed to reveal conceptual linkages and thematic evolution. The findings indicate a growing integration of machine learning approaches in financial risk diagnostics and demonstrate how these technologies contribute to enhancing transparency and predictive accuracy in accounting processes. CZU: [658.15:657.6]:004.8; JEL: G17, M41