POSCO International announced on July 27 that it has successfully completed a proof of concept (PoC) with LG CNS to evaluate trade finance infrastructure powered by blockchain and artificial intelligence (AI). The verification process concluded on July 23 and focused on determining how digital technologies could improve operational efficiency, automate trade processes, and strengthen risk management across the company’s expanding global business network.
The initiative was launched to support POSCO International’s growing international operations by improving the management of transactions and settlements involving overseas subsidiaries. As the company’s global footprint continues to expand, the project also forms part of its broader digital transformation strategy for trade operations.
Pilot program planned after successful proof of concept for digital trade finance
The proof of concept successfully validated the use of blockchain shared ledgers, AI-powered automation, and tokenized real-world assets (RWAs) to modernize trade finance and improve efficiency across global trading operations.
The two companies assessed three primary technology areas during the project: blockchain-based shared ledgers for transaction visibility, tokenization of trade receivables as real-world assets, and AI agents designed to automate document-intensive trade workflows.
The verification process examined whether transaction management, settlement activities, and document review tasks generated during international trade could be digitally integrated and automated. POSCO International supplied its global trade environment and real transaction data to simulate practical business conditions, while LG CNS was responsible for designing the system architecture and validating the blockchain and AI technologies.
One of the key components involved implementing a blockchain-based shared ledger that allows headquarters, overseas subsidiaries, and business partners to access the same transaction information in real time. Previously, transaction data was managed independently by different regional offices or subsidiaries, often requiring repeated verification during contract execution and settlement procedures. The shared-ledger approach demonstrated the potential to minimize inconsistencies in transaction records while improving collaboration and reducing operational risks caused by information discrepancies.
Another major area of evaluation centered on tokenizing trade receivables as real-world assets. Under the proposed framework, receivables generated from actual commercial transactions could be converted into digital assets that are transferable, tradable, manageable, and eligible for settlement through blockchain infrastructure. The companies conducted this portion of the verification using Injective, a blockchain network designed for enterprise financial applications.
The project also assessed whether enterprise-grade compliance requirements could be integrated directly into the blockchain protocol. The evaluation covered permission-based asset management, Know Your Customer (KYC) procedures, Anti-Money Laundering (AML) compliance, investor eligibility verification, and restrictions on asset transfers. The findings were intended to determine whether blockchain technology could support business-to-business receivables management while satisfying regulatory and privacy requirements.
The AI component focused on automating the review of letters of credit (LCs) and other trade documents. AI agents were tested to determine their ability to identify document errors and assist with compliance reviews before transactions progressed further in the trade process.
The AI agent demonstrated its ability to automate document reviews for letters of credit and trade documentation, helping identify errors earlier while reducing inconsistencies caused by varying levels of staff expertise.
International trade documentation often requires specialized knowledge because regulatory requirements and contractual terms differ across jurisdictions, counterparties, and transaction structures. Even minor documentation errors, including typographical mistakes or omitted contractual clauses, can result in delayed settlements or rejected payments. POSCO International expects AI-assisted preliminary reviews to improve document quality while reducing operational differences across its international offices.
Following the successful verification, a company representative indicated that the project had demonstrated the practical applicability of blockchain and AI technologies using real-world trade data and operational processes. The representative added that the company intends to develop a pilot deployment strategy during the second half of the year, focusing on business areas where measurable operational improvements were confirmed.
Following the successful proof of concept, POSCO International plans to prepare a pilot deployment later this year, concentrating on trade finance functions where blockchain and AI delivered the strongest operational benefits.
