DIGITAL TRANSFORMATION OF ACCOUNTING OF TRANSPORT AND LOGISTICS SERVICES BASED ON AI AND BIG DATA

2026

Full text Open access: Hybrid Metadata (CSL-JSON)
DOI 10.32014/2026.2518-1467.1222
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

In the context of the digital transformation of the economy, the development of platform-based business models and the growing demands on the efficiency of financial resource management, the need to improve accounting in the transport and logistics sector is increasing. Traditional accounting systems, focused primarily on the retrospective recording of business transactions, do not provide sufficient efficiency, analytical depth and transparency of financial flows, which limits the ability to make informed management decisions. In this regard, the introduction of artificial intelligence and big data technologies is becoming particularly relevant, allowing to automate accounting processes, integrate diverse sources of information and generate analytical reports in real time. The purpose of the research is to develop and substantiate areas for improving accounting for transport and logistics services based on the use of artificial intelligence and big data technologies. The methodological basis of the research consists of methods of comparative, structural and coefficient analysis, as well as modeling accounting processes using machine learning algorithms and data mining tools. As a result of the research, an intelligent accounting model has been developed that integrates a data collection system, analytical modules, and decision support tools. It has been established that the introduction of AI technologies makes it possible to reduce accounting errors by more than three times, reduce transaction processing time, increase the accuracy of cost classification to a high level and increase the degree of automation of accounting processes. In addition, there was a significant increase in the transparency of financial transactions, a decrease in the proportion of untraceable transactions and an increase in the internal control system. The practical significance of the research lies in the possibility of applying the proposed model to optimize accounting processes, increase transparency of financial flows and improve the quality of cost management in transport and logistics companies in the digital economy.