Automated Tax Compliance for Cross-Border Trading with GRAN-IoT

This project integrates for the first time 5G, IoT, AI, and blockchain technologies for the automated real-time collection of chargeable customs duties and VAT on imports associated with cross-border transactions. By moving tax and customs compliance upstream, closer to the taxable events, the proposed ATTACC system reduces the administration burden on taxpayers, and streamlines the taxation system thereby increasing its reliability and security.


This first-time integration between 5G-based localisation, DLT-based smart contracts and payment systems results in three cardinal assurances necessary for a realistic technical and administrative solution to eliminate frictions and administrative burdens in international trade i.e. Physical delivery (location) assurance, Data/trade documentation assurance and Financial settlement assurance. These assurances enhance the reliability of a cross-border trading system and increase the probability of achieving the claimed market size of digitalisation benefits of US$30bn-40bn in new global trade volume alongside direct saving costs of US$6.5bn.


ATTACC's unique approach integrates novel GRAN-IoT localization with distributed ledger technology and smart data services to achieve real-time, automated tax compliance for cross-border trade. This foundational infrastructure capability delivers IoT tracking, Electronic Trade Documents Act compliance, smart contracts with Open Banking APIs, and AI-enabled risking assurance.

The innovation lies in embedding taxation directly into taxpayers' natural systems rather than as an add-on process. By attaching IoT sensors to goods in a "Russian Doll" hierarchy and using GRAN technology for cross-compatible wireless protocols, ATTACC creates an internationally viable solution that detects taxable events in real-time as goods cross borders and automatically triggers payments. This moves compliance upstream, closer to taxable events, fundamentally transforming tax administration from sequential e-administration to digitally transformed, frictionless taxation.


OECD have set a future vision for tax administration which sets out that future tax administration would increasingly rely on digitisation of processes and innovation in technology. This would mean tax administration is embedded within taxpayer systems, is more real-time, uses the data that is generated within the existing system and uses a resilient network of trusted actors. The proposal presented herein envisions the integration of taxpayer systems with the global supply chain to reduce the complexity and volume of paperwork associated with importing through customs by incorporating novel, GRAN-IoT-based localisation technologies. This brings direct savings of £520m annually. Further direct benefits are associated with reducing the loss of cargo containers in the freight carrier’s system, by way of readily identifying their location; this amounts to 7% per annum loss or damage from a total number of 1.5M ULDs in circulation, totalling US$500m costs savings. Additional opportunities will arise for generating revenue for freight carriers due to the enhanced localisation capabilities for cargo containers. In conclusion, the innovative comprehensive and integrated approach to comprehensive and integrated approach to AuTomated TAx Compliance for Cross-border proposed herein, introduces a first-time foundational infrastructure capability which increases the probability of achieving the claimed market size of digitalisation benefits of US$30bn-40bn in new global trade volume alongside direct saving costs of US$6.5bn. This project will consolidate multiple low and long range wireless technologies, to build, within a Generic Radio Access Network design, cross-compatibility across IoT sensor networks and cross-government jurisdictions which are not aligned in terms of technology adoption. The work will demonstrate the feasibility of the use of technology in cross border trade and impacts on the businesses’ value chain through cost reduction and new markets, in various ways: automate payments for tax and customs duties; speed up the flow of freight through customs at borders and ports; provide a better view of public finances for tax and customs authorities by real-time and more accurate reporting; reduce administrative burden through use GRAN-IoT’s, Distributed Ledger Technology for automated tax compliance, payment systems and APIs; enables end-to-end tracking of goods by carriers and hauliers on behalf of customs and tax authorities, importers and exporters.

Logo for research area

Meet the Principal Investigator(s) for the project

Professor Panos Louvieris
Professor Panos Louvieris - Panos Louvieris is Professor of Information Systems and leads the Defence & Cyber Security (DCS) research group in the Department of Computer Science at Brunel University London and co-director of the Brunel Intelligent Digital Economy and Society (IDEAS) Research Centre. His research interests are data and information fusion, defence and cyber security analytics, and computational finance in the digital economy. He is co-director of the Trusted Open Models Institute (TOMI) at the Hartree Centre concerning the assurance of AI computational models. He is a committee member of the EPSRC Digital Personhood Network. In addition, he is a member of EPSRC ITaaU+ Network and NEMODE+ Network. 

Related Research Group(s)

digital men

Digital Economy - Focusing on international digital economy research capability in areas including cyber security, trust, identity and privacy challenges, and big data analytics.

vr

Intelligent Digital Economy and Society - Research into intelligent digital economy and society using AI, data analytics, 6G, media, human-machine interaction, digital games, augmented and virtual reality, digital twins, IoTs, cyber security, data & information fusion.


Partnering with confidence

Organisations interested in our research can partner with us with confidence backed by an external and independent benchmark: The Knowledge Exchange Framework. Read more.


Project last modified 01/12/2025