DIGITAL TRANSFORMATION OF CUSTOMS ADMINISTRATION FOR UKRAINE’S ECONOMIC RECOVERY: A CONCEPTUAL MODEL OF "SMART CUSTOMS 2.0"

Abstract

The article substantiates the role of the digital transformation of customs administration as an infrastructural prerequisite for accelerating firms’ foreign economic activity. The research aims to develop a conceptual model of “Smart Customs 2.0,” combining a service-oriented approach for compliant businesses with enhanced risk-based controls to counter violations and security threats. The methodological framework includes an analysis of international approaches to digital customs and trade facilitation, the systematization of technological solutions, and the design of a process architecture with cross-level data interaction. A four-level hierarchical structure is proposed: a foundational level of physical control and data collection; a data and information security level; an analytical level; and a strategic and service solutions level. The model’s levels are specified through typical digital tools, including non-intrusive inspection and border sensors, centralized data repositories, cybersecurity measures, explainable AI-based risk scoring, and digital services for businesses. A key feature of the model is an adaptive “feedback loop” that dynamically adjusts inspection parameters based on control outcomes and service requests, thereby improving targeting accuracy and reducing unjustified delays. For performance evaluation, time-to-release indicators from the Time Release Study (TRS) methodology are proposed, combined with digital customs KPIs (share of automated decisions, share of inspections, inspection effectiveness, and stability of risk models). Special emphasis is placed on the need for data interoperability and integration with electronic services and interagency registers, which should improve logistics predictability and the quality of managerial decisions. The article shows that implementing “Smart Customs 2.0” can lower transaction and logistics costs, shorten capital turnover time, and enhance operational transparency and supply chain resilience, which is critical during Ukraine’s post-war recovery and alignment with European standards for customs data exchange. The scientific novelty lies in the integrated combination of TRS measurement, data architecture, and explainable risk scoring within a single process management model. The practical significance of the research consists in formulating requirements for data interoperability, cybersecurity, and change management to implement digital customs services. It is noted that the model’s effectiveness depends on data quality and AI model governance procedures, which must be considered at the implementation stage.