DIGITAL FINANCIAL MONITORING AS AN INSTRUMENT FOR DECISION-MAKING IN PUBLIC ADMINISTRATION

This study comprehensively investigates the integration of Artificial Intelligence (AI) technologies into the digital financial monitoring system within the context of enhancing decision-making efficiency in public administration. The relevance of this issue is determined by several key factors. Firstly, the increasing complexity of tasks faced by public authorities in managing financial resources necessitates the application of novel and more powerful tools for analysis and control. Secondly, the digitalization of the economy and society opens up broad opportunities for automating routine operations, identifying hidden patterns, and forecasting future trends in the financial sphere. Thirdly, in the context of the state of war and the post-war recovery of Ukraine, ensuring transparency and accountability in the use of budgetary funds, as well as the effective management of financial planning and control processes, acquires particular significance. The role of AI in ensuring key principles of public governance, such as transparency, accountability, and efficiency, is considered. It is emphasized that AI can be utilized for automating the collection and processing of large volumes of financial data, detecting anomalies and fraudulent transactions, forecasting financial indicators, and evaluating the effectiveness of budgetary programs. Particular attention is paid to the possibilities of applying AI to enhance analytical support for the decision-making process at various levels of governance – from local to national. Concrete examples of the implementation of intelligent technologies in the financial sphere of Ukraine are provided. Specifically, the experience of using AI in banking institutions for credit risk assessment, anti-money laundering detection, and the automation of customer service processes is examined. The possibilities of applying AI to increase the efficiency of electronic public procurement systems (ProZorro) and open data on the use of public funds (Spending.gov.ua) are analyzed. The article also presents an overview of the European Union countries' experience in the field of AI application for financial monitoring, particularly in the context of combating corruption and ensuring financial stability. The challenges and risks accompanying the process of digital transformation of the public financial sector are considered. These include problems of ensuring information security, including protection against cyber threats and unauthorized access to confidential data; ethical aspects of AI use, related to potential biases in algorithms and insufficient transparency in decision-making; the problem of insufficient digital literacy of officials, which may complicate the effective use of new technologies; as well as the problem of fragmented information systems, which hinders data integration and comprehensive analysis of financial information. A set of recommendations covering various aspects of AI implementation in the field of financial monitoring is proposed. These recommendations include: the development of a clear strategy and action plan for AI implementation; the creation of specialized AI analytics units in public authorities; the organization of training and professional development of personnel in the field of AI; the development of ethical codes and standards for AI use; ensuring interoperability between different information systems; ensuring the transparency and understandability of AI algorithms; the development of a methodology for evaluating the effectiveness of AI implementation; as well as strengthening measures to ensure cybersecurity and data protection. It is underscored that the integration of AI into financial monitoring is a promising direction for the development of public administration, which can contribute to enhancing its efficiency, transparency, and accountability. At the same time, the necessity of a comprehensive approach to AI implementation, taking into account not only technical but also organizational, legal, and ethical aspects, is emphasized. The article also identifies promising areas for further research in this field, including the development of a methodology for ethical auditing of AI algorithms, the adaptation of AI models to the specifics of different levels of governance, the development of tools for public oversight of AI use (CivicTech), the evaluation of the economic and social effectiveness of implemented solutions, as well as a comparative analysis of international experience in the application of AI in financial monitoring.