Digital technologies in combating corruption: conceptual approaches in the system of public administration and finance

Abstract

The article is devoted to the study of conceptual approaches to the use of digital technologies in the fight against corruption in the system of public administration and public finances. The relevance of the topic is due to the growing role of digitalization as one of the key tools for increasing transparency, accountability and efficiency of state authorities in the context of institutional transformations. The purpose of the article is to systematize and comparative analysis of the main conceptual approaches to the use of digital technologies in anti-corruption policy. The study identifies five methodological approaches: the digital transparency approach, institutional-automation, analytical-preventive, public-participatory and legal-technological. It is shown that the digital transparency approach is based on data openness and digital fixation of management processes, which reduces the level of information asymmetry and enhances financial accountability. Results. The institutional-automation approach is aimed at minimizing the human factor by automating administrative and financial procedures. The analytical-preventive approach reveals the potential of using big data and risk analysis algorithms for early detection of corruption schemes. The public-participatory approach focuses on digital mechanisms for involving citizens in monitoring the use of public finances, while the legal-technological approach involves the integration of digital tools directly into the anti-corruption legal system. Conclusions. It is concluded that effective counteraction to corruption is possible only if the above approaches are applied comprehensively, taking into account the institutional environment, legal regulation and the level of digital maturity of the state. Recommendations are formulated to increase the effectiveness of digital anti-corruption mechanisms, in particular in the field of public finances.