White Paper Trade Tech

The document argues that archaic, paper-based processes create a significant trade finance gap, particularly for SMEs and emerging markets, which was estimated at $1.5 trillion in 2017. It posits that distributed ledger technology (DLT), combined with AI, IoT, and smart contracts, can reduce operating costs by 50-70% and facilitate approximately $1.1 trillion in new trade volumes globally by 2025. The report details various stakeholder responses—from banks forming consortiums like we.trade to governments implementing 'single window' electronic systems—and emphasizes that widespread adoption requires coordinated ecosystem change and the harmonization of standards.

• A substantial global trade financing gap existed in 2017, totaling approximately $1.5 trillion, which represents about 10% of global merchandise trade volumes. This gap is primarily driven by the needs of small and medium-sized enterprises (SMEs) and midcap companies, who account for 75% of the total gap.
• Without intervention, the trade finance gap is projected to exceed $2.4 trillion by 2025. However, the adoption of digital technologies, specifically distributed ledger technology, is estimated to potentially facilitate $1.1 trillion in new trade volumes globally.
• Traditional trade finance is hindered by high operational costs, with a typical cost-to-income ratio of 50-60%. Distributed ledger technology could potentially lower these operating costs by 50-70% and improve turnaround times by three to four times.
• The digitalization of border processes can lead to dramatic efficiency gains. In Senegal, the implementation of an electronic single window reduced border preclearance and clearance processing time by 90%, moving from an average of two weeks to one day, and decreased the cost of border processes by 60%.
• The integration of DLT with other technologies provides specific functional advantages: tokenization enables digital identity for goods; smart contracts automate delivery and payment synchronization; IoT devices reduce data tampering risks; and AI tools can predict working capital requirements.
• Widespread adoption of these technologies faces three primary challenges: the need for cost-benefit justification for investment, security and energy efficiency risks associated with scaling distributed databases, and the requirement for coordinated change and interoperable standards across the entire ecosystem of buyers, sellers, shippers, governments, and banks.

APA

World Economic Forum (2018). White Paper Trade Tech. http://www3.weforum.org/docs/White_Paper_Trade_Tech_report_2018.pdf

Chicago

World Economic Forum. White Paper Trade Tech. 2018. http://www3.weforum.org/docs/White_Paper_Trade_Tech_report_2018.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=White Paper Trade Tech |date=September 2018 |url=http://www3.weforum.org/docs/White_Paper_Trade_Tech_report_2018.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2018white, author = {{World Economic Forum}}, title = {{White Paper Trade Tech}}, institution = {World Economic Forum}, year = {2018}, month = sep, url = {http://www3.weforum.org/docs/White_Paper_Trade_Tech_report_2018.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }