Tracing Mongolia's Mineral Wealth: A Framework for an AI-Enabled Digital Monitoring System for Natural Resource Exports

Mongolia earns almost all of its export income from a few raw minerals shipped to a single neighbour, yet no public system shows, in near real time, what physically leaves the country, what it contains, where it goes and who is paid for it. In 2024 coal and copper concentrate made up about 74% of export value and China received 91% of exports. This working paper argues that existing transparency tools, including EITI reporting, customs statistics, the minerals cadastre and the Mining Products Exchange, rely on declarations and cannot verify physical volumes or mineral content. Drawing on the literature on the resource curse, trade misinvoicing and mirror statistics, and on advances in satellite monitoring, border assay and traceability, it proposes an AI-enabled Digital Resource Monitor: a three-layer system that measures physical flows, reconciles them with declared data using machine learning, and publishes results openly. The paper sets out the system architecture, a phased pilot starting with coal and copper concentrate, governance and ethical safeguards, and the system's relevance to other resource-rich countries and to EU due-diligence and critical raw materials rules.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-28
DOI
https://doi.org/10.5281/zenodo.23007533
Primary Topic
Mining and Resource Management
Type
article
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Tracing Mongolia's Mineral Wealth: A Framework for an AI-Enabled Digital Monitoring System for Natural Resource Exports

Enkhtsetseg Shirendev
Zenodo (CERN European Organization for Nuclear Research)
Mining and Resource Management
article

Tracing Mongolia's Mineral Wealth: A Framework for an AI-Enabled Digital Monitoring System for Natural Resource Exports

Enkhtsetseg Shirendev
article en

Abstract

Mongolia earns almost all of its export income from a few raw minerals shipped to a single neighbour, yet no public system shows, in near real time, what physically leaves the country, what it contains, where it goes and who is paid for it. In 2024 coal and copper concentrate made up about 74% of export value and China received 91% of exports. This working paper argues that existing transparency tools, including EITI reporting, customs statistics, the minerals cadastre and the Mining Products Exchange, rely on declarations and cannot verify physical volumes or mineral content. Drawing on the literature on the resource curse, trade misinvoicing and mirror statistics, and on advances in satellite monitoring, border assay and traceability, it proposes an AI-enabled Digital Resource Monitor: a three-layer system that measures physical flows, reconciles them with declared data using machine learning, and publishes results openly. The paper sets out the system architecture, a phased pilot starting with coal and copper concentrate, governance and ethical safeguards, and the system's relevance to other resource-rich countries and to EU due-diligence and critical raw materials rules.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 15%
Mining and Resource Management
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