ОБЛІКОВО-ФІНАНСОВЕ ЗАБЕЗПЕЧЕННЯ СИСТЕМИ ФІНАНСОВОЇ БЕЗПЕКИ АГРОПРОМИСЛОВИХ ПІДПРИЄМСТВ У ЦИФРОВІЙ ЕКОНОМІЦІ

In the globalized business world, financial information security management (FISM) and corporate risk management (CRM) have become critical elements for ensuring business sustainability and gaining a competitive advantage. The security of financial information not only protects the financial integrity of businesses but also supports long-term success by enhancing reputation management, regulatory compliance, and stakeholder trust. However, the necessity of addressing the relationship between financial information security and corporate risk management within a holistic framework has not been sufficiently emphasized in the literature, especially with the increasing threats in cybersecurity. This gap creates uncertainties regarding how businesses should integrate financial information security into their risk management strategies. The purpose of this study is to analyze the interaction between financial information security management and corporate risk management and to provide a practical and applicable framework for integrating financial information security into business risk management strategies. The study examines how financial information security management is integrated into corporate risk management processes (risk identification, assessment, response, and monitoring) and its impact on organizational performance (cost reduction, efficiency improvement, and competitive advantage). Considering major financial crises and cyberattacks, the global impact of financial information security threats on businesses, national economies, and the global financial system is increasingly being discussed. In this context, the study highlights the critical importance of FISM and CRM for businesses and presents concrete examples of the risks that may arise if these two concepts are not considered together (data breaches, financial losses, reputational damage, legal sanctions). The study systematically reviews existing approaches in the literature (such as ISO 27001 and the NIST Cybersecurity Framework) to contribute to the development of effective financial security and risk management policies for businesses.This study employs qualitative research methods, including a literature review and expert opinions. By analyzing current studies and industry reports, the relationship between financial information security and corporate risk management is examined in depth.In conclusion, integrating financial information security management with effective corporate risk management policies plays a crucial role in enhancing business sustainability, gaining a competitive advantage, and reducing costs. Businesses must adopt a holistic management approach that incorporates cybersecurity measures, financial risks, and regulatory requirements. This comprehensive approach is essential for ensuring long-term success and maintaining a competitive edge in today's dynamic business environment.

In the article, the authors analyze Russian and foreign scientific literature dealing with financial security in solving the problems of ensuring the economic security of an enterprise. The aim of the study is to compare Russian and foreign approaches to assessing financial security as one of the components of the economic security of an enterprise. Research methods: information search; systematization; logical, system and content analysis. The authors come to the conclusion, that in foreign scientific literature, “financial security” is understood as “financial stability”, and such a term as “financial management” is also used. At the same time, the indicators used by foreign researchers to assess the financial condition of an enterprise do not differ significantly from those used by Russian scientists, because in fact indicators of both financial security and financial stability are built upon indicators of economic analysis.

Summary. The article examines the linkages between financial stability and the level of its economic security. Considered the content of financial stability, represented by its own definition, we studied the basic conditions to achieve it. The logic diagram showing the location of financial stability and financial security to ensure the economic security of the business entity. A system of internal and external factors affecting the financial stability and endanger financial stability and financial security company. It has been established that it is the internal factors such as the availability of financial resources and financial position, capital structure, the company's ability to generate profits determine the level of economic security and its ability to withstand the negative impact of external and internal threats. The necessity of improving the financial sustainability in order to improve the economic security of the enterprise. On the basis of the research proposed matrix of risks affecting the financial stability and economic security, which allows to determine the probability of their occurrence and impact. It presents the economic, social, human, financial, organizational, economic, innovative and productive tools to increase the stability and financial security of an economic entity. List considered standard measures will make a plan of action to minimize the adverse impacts and enhance financial stability and security. Therefore, a prerequisite for the economic security of the enterprise is the attainment of financial stability.

Under the wave of digital transformation, financial risks have shown unprecedented complexity and dynamism, which not only brings new challenges but also highlights the urgency of building a cognitive and evolving financial risk monitoring and early warning security system. Financial risk management, as the key to maintaining financial market order, safeguarding consumer rights, and promoting financial innovation, its core value lies in ensuring the stable operation of the financial system and the sustainable development of the economy. With the rapid growth of artificial intelligence (AI) and big data technology, these advanced technologies are profoundly changing the management mode of enterprises, especially showing significant advantages in improving the level of financial risk management. This article innovatively designs an enterprise financial risk prediction model that integrates AI and big data technology. The model aims to provide more accurate risk avoidance strategies for enterprises by deeply mining and analyzing massive transaction data. The results show that the model not only improves the accuracy of risk prediction, but also provides strong support for enterprises to move forward steadily in the complex and ever-changing financial market.

In the past, financial risk management has always faced a changing market environment and while there were several traditional predictive models available for use, they have limited capabilities in addressing non-linear or high-dimensional risk factors. Therefore, enhancing the foresight in risk identification as well as the accuracy of decision-making within financial institutions will require further exploration into the application value of artificial intelligence and big data technology. Consequently, the goal of this paper is to conduct a comprehensive evaluation regarding the integration pathways and effectiveness of implementing these two technologies into financial risk predicting and managing practices. Findings from the research indicate that AI algorithms offer a deeper understanding of complex, hidden relationships among large amounts of multiple sources of information, while the availability of big data platforms provides opportunities for continuously monitoring risk in real-time. The combination of the two not only significantly improves the timeliness and accuracy of risk prediction, but also promotes the intelligent transformation of risk management models from passive response to active intervention.

The agribusiness sector is a cornerstone of national and global economies, encompassing the production, processing, marketing, and distribution of agricultural goods. Effective financial management within agribusiness is critical, as it directly influences resource allocation, investment decisions, risk mitigation, and overall enterprise sustainability and profitability. This study conducts a comprehensive literature-based analysis to examine how financial management practices bridge finance and farming, focusing on cost management, working capital management, financial risk management, investment appraisal, digital finance adoption, financial literacy, and corporate social responsibility (CSR). Evidence from diverse geographic and operational contexts demonstrates that structured financial practices significantly enhance profitability, operational efficiency, and resilience in the face of seasonal cash-flow fluctuations, price volatility, and environmental risks. Cost management aligns operational efficiency with strategic financial planning, while working capital management ensures liquidity and continuity during peak production periods. Financial risk management and CSR integration mitigate exposure to market and environmental uncertainties, promoting sustainable practices and stakeholder trust. The adoption of digital finance tools and platforms further strengthens the interface between financial planning and farm operations, although constraints such as low digital literacy and infrastructure limitations persist. Moreover, financial literacy among small-scale farmers emerges as a key enabler, facilitating the effective utilization of financial tools and resources. Investment decision-making frameworks incorporating scenario analysis and real-options valuation support informed capital allocation and long-term growth. Overall, the study underscores that bridging finance and farming is operationally vital, multi-dimensional, and strategically essential for achieving sustainable agribusiness growth. Insights from this analysis inform policymakers, practitioners, and researchers seeking to optimize financial management strategies in agribusiness contexts.

Systemic risks are relevant to most segments of financial and economic activity, which creates the threat of financial instability of enterprises. Financial security, in this case, implies the state of financial soundness; it is expressed through various parameters including the level of solvency, financial stability, business activity, and efficiency of management. These questions are specific to each indicator, and this paper aims to understand their relations and how changes in them can result in risks. It elaborates the risk analysis and assessment procedure that uses a set of common financial analysis tools and determines key financial coefficients. Liquidity ratios, solvency ratios, profitability ratios, and the risk exposure metrics are the key areas that the research is based on. Correlating the financial indicators from a rich dataset from Yahoo’s Stock market data, regression analysis is used to determine these relationships between these indicators and risk management factors. A positive relationship between liquidity ratios and profitability is detected points to the fact that, firms with high liquidity levels are more capable of attaining good financial health and returns. It establishes the need for the development of a credible risk management structure that would lower threats to fiscal and economic activities. In light of this, the research shows that the liquidity and solvency management lowers financial risk and improves return for companies. The regression analysis was conducted to ascertain the degree of predictability of each independent variable to the dependent variable and the findings revealed that approximately 94 percent of each independent variable is predictable of the dependent variable that able to establish as much as 5% of the total variability in profitability, with the PE ratios being an indication of this aspect, was attributed to stock prices, as a result, the firm must be keen on its financials. This paper explores the employability of the proposed methods and models to assess the risks with high accuracy and supports optimum decision making in regard with the needed security of the enterprises. By adopting these methodologies, the businesses can observe and estimate risks which exist in the future which would help them to avoid certain issues or dangers and also pave the way for the improvements of the financial stability of the businesses. On this note, the study establishes the fact that incorporating the notion of total risk management into the framework of analyzing business and making financial decisions is inevitable in maintaining corporate financial stability and realizing perpetual economic solidity. This research enriches the literature on financial risk management, as it outlines viable strategies for the protection of enterprise financial sustainability.

The rapid advancement of artificial intelligence (AI) technologies, particularly generative AI and large language models (LLMs), has ushered in a new era of possibilities for the financial sector. This paper explores the integration of these cutting-edge technologies into financial sector risk management, examining both the potential applications and the necessary regulatory frameworks. We provide a comprehensive analysis of how generative AI and LLMs can revolutionize risk assessment, fraud detection, market analysis, and regulatory compliance. The study delves into the technical aspects of these AI models, their implementation challenges, and the implications for existing risk management practices. Furthermore, we propose a novel framework for the responsible adoption of AI in financial risk management, addressing concerns related to model interpretability, data privacy, and algorithmic bias. Our findings suggest that while generative AI and LLMs offer unprecedented opportunities for enhancing risk management capabilities, they also necessitate a recalibration of regulatory approaches to ensure financial stability and consumer protection. This research contributes to the growing body of literature on AI in finance and provides actionable insights for practitioners, policymakers, and researchers in the field.

With rapid development of China's market economy, business activities face many risks. The core of the overall management and control of risk is the company's financial risk management. In order to prevent financial risks caused by business management crisis and promote corporate healthy steady sustainable development, the focus on financial risk management and control is a possible series of financial problems and risk to predict and control in the future. In this paper, based on the financial risk characteristics of Chinese enterprises and the management and control situation, in the new period, we strengthen risk awareness, improved scientific financial decisions and build financial risk management and control system by analysing impact factors of financial risk in China to put forward the corresponding management and control strategies.

With the continuous development of the times, the business scope of the financial market is also expanding, and more and more unknown risks have emerged in the process of development, which has brought a certain impact to the financial market. The exchange rate fluctuation, interest rate and other factors related to the international financial market make financial market risk one of the important risks faced by securities companies. Therefore, securities companies need intuitive, accurate and effective quantitative management tools for financial market risk assessment to improve the overall risk management level of the company. Therefore, this paper constructs a financial market risk prediction system based on computer data simulation technology and Markov chain Monte Carlo algorithm. This system is mainly composed of three parts: financial risk management, data exchange management and background risk application services. The front end of the financial market risk prediction system is divided into risk monitoring, risk allocation, risk report, risk decision-making and system log modules according to functions. Data collection management functions mainly include data collection, data encryption, data conversion, data return and other functions. The measured results show that the system can predict the significant inflection points in most economic risks synchronously or in advance, and the forecast data show that the financial security index has an upward trend from bottom to top. In this paper, the Markov chain Monte Carlo algorithm is introduced into the financial market, through data simulation to predict the risks of companies with economic risks and make a small contribution to the market development.

The motivation for this research was the desire to disclose the social nature of the financial risks of global companies: the authors attempted a scientific explanation of the influence of corporate social responsibility, which is manifested through the preservation and creation of additional jobs, on the financial risks of global companies. The research aims to establish the interdependence between financial risks and sustainable employment in global companies. This goal is achieved using the SEM (structural equation modeling) method based on corporate statistics from the Fortune “Global 500” rankings for 2021–2023. As a result, the consequences of global companies’ CSR (corporate social responsibility) practices in personnel management and financial risk management are modeled and described through quantitative and qualitative patterns. The established regularities proved that for developed and developing countries, the larger the number of employees, the lower the financial risks of global companies—the risk of a decrease in profitability, the risk of loss of profit, and the risk of depreciation of assets. The main conclusion is that there is a close systemic relationship between the financial risks of global companies and their workforce size, suggesting that CSR is key to highly effective financial risk management. A clear distinction between the practices of financial risk management through CSR in developed and developing countries forms the basis of the theoretical significance of the research results. The authors provide recommendations to improve the current practice of financial risk management in global companies by integrating it more closely with personnel management practices, highlighting their managerial relevance. It is proposed that corporate strategies for global companies in developed countries should focus on reducing the risk of declining profitability, as CSR has the most pronounced and consistent impact on this particular financial risk. In developing countries, corporate strategies are recommended to be structured by diversifying the areas of CSR application, with the most promising in financial risk management being the reduction in asset depreciation risk and the reduction in profitability risk. The findings of this research have practical significance because they enhance the predictability of CSR activities of global companies and open up opportunities for highly accurate forecasting of the financial risk implications of ensuring sustainable employment by global companies, considering the specificities of developed and developing countries.

The methodological and practical recommendations for applying a conceptual approach to forming an effective mechanism for managing financial security at business enterprises under conditions of economic recovery are substantiated. Despite the existence of some proposals for forming effective mechanisms for managing financial security at the level of market participants, the practice of implementing and arranging their components by stages and distribution by functional performers is a matter of active discussion in academic circles. The ontological content of the scientific category “financial security of enterprise” at the macro and micro levels is generalized. The author focuses on the need to consider the enterprise's financial security as an integral management system with an internal structure, elemental composition and feedback components. The components of the enterprise financial security management system are specified. The author's own interpretation of the essence of the concept of “enterprise's financial security management mechanism” as a set of tools and levers of influence on managerial decision-making in the field of ensuring an appropriate level of protection of vital financial interests of a market entity from challenges and threats of the external environment is proposed. The stages of forming a financial security mechanism at business enterprises are recommended, including: analysis of the enterprise's current status, development of a strategy to overcome the identified risks, implementing measures, monitoring and evaluating the implemented measures. At the conceptual level, the author's version of the mechanism for managing financial security of the business enterprise with the appropriate support tools (financial instruments, financial levers, financial methods and indicators, information and analytical subsystem) and four key components (organizational, methodological, technological and financial) is proposed. Promising directions for improving the organizational support of the financial security management mechanism at business enterprises with the assignment of responsible managers and specification of the timeframe for implementing measures are identified. The expediency of distributing responsibility among the specialists for the financial subsystem at business enterprises is substantiated.

Financial and economic activity is exposed to numerous systemic risks, which are a threat to the financial security of enterprises. The criterion for ensuring financial security is the appropriate level of the company's financial condition. The financial condition of the enterprise is a complex concept and is characterized by the system of indicators – financial coefficients: indicators of liquidity, financial stability, business activity, and management efficiency. The interrelationship and mutual determination between the indicators that cause the occurrence of risk when one of them changes is established.A range of factors that comprehensively characterize the financial and economic activity of the enterprise has been determined and developed risk analysis and assessment methodology, which includes the following stages: preparatory stage; construction of an algorithm for quantitative assessment of risk in the financial security system; interpretation of the results of an integrated risk assessment in the financial security system; determining the priorities of risk management in the system. The methods of financial analysis (horizontal, vertical, coefficient, analysis of business activity and financial stability) were applied and a quantitative assessment of risks was carried out. The indicators-coefficients of the enterprise's functioning are calculated and given an interpretation.The conclusion was formed that the construction of an effective risk management system and its universal functional component of risk analysis are current issues, as they allow to develop a set of measures to minimize threats and risks of conducting financial and economic activities of economic entities. Therefore, the correct assessment of risk with the help of the proposed methods and models of financial analysis for individual economic situations and business entities is effective and has value, as it gives the opportunity to make the optimal decision in specific situations and characterizes the criterion feature of financial security of industrial enterprises – liquidity, financial stability, business activity, profitability.

The article examines the role of accounting digitalization and the development of digital audit in the system of using financial instruments for price risk hedging in international markets. It is determined that in the conditions of globalization of economic processes, instability of global commodity and financial markets, and increasing price volatility, the need for effective financial risk management tools is significantly increasing. Particular attention is paid to the impact of the digital transformation of the economy on the development of accounting and auditing, as well as to the use of modern information technologies, including cloud services, Big Data technologies, artificial intelligence, and blockchain for processing financial information and ensuring the reliability of financial reporting. The study analyzes the essence and key characteristics of digital accounting and digital auditing and identifies their main functions and differences in the system of financial information management. The paper also characterizes the main financial instruments used for price risk hedging in international markets, including forward and futures contracts, options, swaps, and other derivative financial instruments. In addition, modern software solutions used for accounting, risk management, and financial control are considered, particularly enterprise resource planning (ERP) systems and analytical platforms used by international companies and financial institutions. It is substantiated that the use of digital technologies in accounting and auditing contributes to improving the transparency and reliability of financial information, increasing the efficiency of financial control, and ensuring the operational processing and analysis of large volumes of financial data. Digital solutions also create favorable conditions for monitoring financial transactions, assessing market risks, and supporting informed managerial decision-making. The development of digital accounting and digital audit tools forms an important information basis for the effective use of financial instruments for price risk hedging and enhances the stability of enterprises operating in the global financial environment.

Chinese financial market environment has also undergone a series of changes. How banks can identify and effectively prevent and control financial risks has become the focus of their research. For this reason, this paper makes a careful study on the management ideas of bank financial risk, first introduce the relevant content and characteristics of bank risk identification and management, explaining the new requirements and challenges brought about by the bank's financial risk management under the current background, and focus on analyzing the relatively representative issues in the financial risk management of banks in various regions, finally, it puts forward the strategies and improvement ideas on how to improve the quality and efficiency of bank risk management.