Transitioning from Paper to Electronic Trade Documents: The Need for Reliable Physical Assurance

Authors:
Preprint
Publisher website
Google Scholar
Abstract
The transition from paper-based to electronic trade documents (eTDs) represents a critical step in modernising global supply chains; however, the absence of reliable mechanisms to verify the physical movement of goods vis-a-vis the eTD workflow remains a significant challenge. This study proposes the PROGRESS framework, an integrated digital trade architecture that combines AI-driven document verification with real-time physical tracking to ensure end-to-end assurance of consignments. The approach leverages advanced Optical Character Recognition (OCR) techniques, including Transformer-based attention models, Convolutional Recurrent Neural Networks (CRNN) with Connectionist Temporal Classification (CTC), and Vision Transformers (ViT), enhanced through context-aware validation to ensure semantic consistency across key trade documents such as commercial invoices, packing lists, airway bills, and certificates of origin. A simulation involving 5,100 consignments was conducted and benchmarked against real-world operations at Teesside International Airport. Results indicate that the proposed system reduces document processing time from 24–72 hours in traditional paper-based systems to approximately 1–2 minutes, achieving a validation accuracy of 98%. Furthermore, integration with RFID-based tracking, geofencing, and private 5G connectivity enables continuous monitoring of consignments, reducing customs dwell times from 72 to 44 hours and increasing throughput by up to 65%. The findings demonstrate that combining digital documentation with verifiable physical assurance significantly enhances transparency, efficiency, and regulatory compliance. This research contributes to the advancement of digital trade by addressing key limitations in current eTD implementations and supporting the effective adoption of the United Kingdom’s Electronic Trade Document Act.

This publication has 37 references indexed in Scilit: