Innovative Technologies in Anti-Corruption Audit.

Subject of study. The implementation of innovative technologies (artificial intelligence, big data analytics, blockchain, machine learning) into anti-corruption audit systems as a mechanism for transforming traditional financial control methods. The composition and structure of technological solutions for detecting, preventing and minimising corruption risks in public and private sectors. The aim of the study. Theoretical substantiation and development of conceptual and methodological foundations for implementing innovative technologies into the anti-corruption audit system to improve the effectiveness of detecting, preventing and minimising corruption risks, including the development of practical proposals aimed at transforming audit procedures from reactive to proactive monitoring instruments. Research methods. The methodological basis of the study includes a set of scientific methods: systematic analysis of modern approaches to anti-corruption audit, structural-logical modelling of technology implementation stages, comparative analysis of traditional and innovative audit methods, synthesis of international best practices in applying digital technologies to combat corruption, and systematisation of empirical data on the effectiveness of AI, big data and blockchain in audit processes. Results of work. The study provides a comprehensive analysis of traditional anti-corruption audit problems and corresponding innovative technological solutions. A structural-logical implementation scheme has been developed, encompassing four sequential stages: preparatory, pilot implementation, scaling, and continuous improvement. The key implementation principles have been identified: systematicity (comprehensive integration of all technologies), gradualism (phased implementation without abrupt changes), transparency (openness of processes and results), and continuity (constant improvement). The need to integrate technologies into a unified national anti-corruption audit platform with modules for procurement monitoring, risk forecasting, and data verification via blockchain has been substantiated. The main implementation challenges have been determined: technological barriers, organisational obstacles, regulatory limitations, ethical issues of AI use, and high initial investments. Research perspectives are outlined concerning the development of specific methodologies for evaluating the effectiveness of innovative technology implementation and creating industry standards for their use in anti-corruption audit.