Integration of multi-agent systems and blockchain platforms for automating financial transactions using graph topological analysis

Abstract

This article is devoted to the integration of multi-agent systems and blockchain platforms for automating financial transactions using graph topological analysis. The introduction substantiates the relevance of the work, linking modern requirements for the security and transparency of financial processes with the need to use distributed technologies. It is explained that multi-agent systems with flexibility and adaptability, combined with the immutability and decentralization of blockchain technologies, can significantly improve the efficiency of digital financial ecosystems. The methods section presents a developed methodology that includes modeling financial transactions in the form of graph structures, which allows topological analysis to be used to identify key nodes and vulnerabilities in the network. The stages of software development, the use of clustering and optimization algorithms, as well as the integration of a blockchain platform to ensure data transparency and security are described. Special attention is paid to the formalization of criteria for the reliability of the system, the definition of metrics for assessing the stability and effectiveness of automated financial transactions. The results section provides data from experimental tests of the model, demonstrating improved throughput and reduced time costs during transactions. The analysis of the constructed graphs revealed correlations between the structural characteristics of the network and the increase in transactions, which allowed optimizing the allocation of resources within the system. The effectiveness of the proposed approach is confirmed by a comparative analysis with traditional methods of financial process management. The discussion focuses on the prospects of integrating multi-agent systems and blockchain technologies to create scalable and secure solutions in the financial sector. Comparisons are made with modern research, and areas for further development are identified, such as expanding the functionality of topological analysis algorithms, improving agent adaptability, and increasing the degree of decentralization of the system. The author concludes that the synergy of the technologies considered opens up new opportunities for automation and optimization of financial transactions, contributing to the creation of a reliable and sustainable digital infrastructure of financial services.