Latest move in a bid to close the growing trillion-dollar trade finance gap
13 April 2023 - Global Shipping Business Network (GSBN), an independent, not-for-profit technology consortium building a blockchain-enabled operating system designed to redefine global trade, announced that it has completed a ground-breaking proof-of-concept with HSBC to harness confidential computing technology through Decentriq Data Clean Rooms to transform global trade finance.
Trade finance is the lifeblood of global trade, yet the financing gap is estimated to reach US$2.5 trillion by 2025, according to the World Economic Forum. One of the reasons why funding applications are rejected is due to the lack of information from the requesting entities. HSBC, as one member of GSBN’s Trade Finance Advisory Group, has responded to the unmet demand by collaborating on a number of solutions and proof-of-concepts that harness trusted digital data from the supply chain.
To better serve customer needs in trade finance, banks must first understand client’s business by looking into their working capital cycle, trade routes, counterparties, etc. Currently, this information can only be obtained by asking customers to produce a checklist of paper documents from various parties such as bill of ladings, invoices, contracts, etc. This lengthy process not only becomes an administrative burden for all parties involved, it also increases review time.
Confidential computing is the latest in privacy-enhancing technology designed to protect data at the hardware level. While GSBN’s platform is built upon blockchain technology with strict access policies, there are scenarios that require more complex data collaboration processes. Trade finance is one such scenario in which banks need alternative and aggregated insights from various entities involved in the supply chain of a customer to build a holistic understanding. In particular, shipment records can shed lights on business operations in terms of volume and business nature, which are valuable insights that help banks tailor appropriate financing solutions that cater to the working capital needs of their customers.
The latest proof-of-concept unlocks a brand-new way of data collaboration that allows the aggregation of shipping records across shipping lines through the use of a data clean room, which is a solution provided by technology partner, Decentriq, harnessing confidential computing technology. In the proof-of-concept, synthetic shipment details provided by carriers via GSBN are aggregated and processed in the clean room, where HSBC can access the statistics to gain a better understanding of customers’ shipping activities, i.e., number of shipments, distribution of cargo nature, and average cargo quantity etc.
Not only does this strip away sensitive or unnecessary information, displaying only the necessary statistics and insights to the bank for its assessment, it also increases the representativeness of the statistics enabled by the aggregation of data across multiple parties. Moreover, the combined use of blockchain and confidential computing technologies ensures ease of insight sharing while maintaining a high level of privacy, security, and auditability throughout the data lifecycle.
Bertrand Chen, CEO at GSBN, said, “This latest collaboration with HSBC demonstrates GSBN’s unique position not only as a trusted data utility platform, but also as a liaison between banks, carriers and other stakeholders to explore new value-adding applications. We will continue to collaborate with our members and partners to expand the applications of confidential computing technology.”
Aditya Gahlaut, HSBC Managing Director and Head of Global Trade and Receivables Finance, Hong Kong and Macau, said, “Alternative data opens a new path to simplifying trade finance as it allows banks to gain more timely, accurate and relevant insights of clients’ activities. We will continue to leverage the latest technology and collaborate with different stakeholders in the industry to make trade finance faster, easier and more accessible for importers and exporters.”
Maximilian Groth, CEO & Co-Founder at Decentriq, said, “The success of this proof-of-concept shows that blockchain and confidential computing technologies are complementary in a commercial setting by delivering next-generation privacy, security and auditability throughout the data cycle. We look forward to expanding data clean rooms to members across GSBN’s global trade ecosystem.”
Incorporated in Hong Kong, the Global Shipping Business Network (GSBN) is an independent, not-for-profit technology consortium to build a blockchain-enabled operating system to redefine global trade. The platform facilitates trusted collaboration between disparate and competing market participants, as well as enabling greater efficiencies and resilience. It also aims to expand the global trade ecosystem by creating bridges to new market participants including banks, fintech companies and other consortia, while supporting the development of technology-driven innovation as the sector makes the leap to digital.
The consortium was first founded by 8 global leaders in the global shipping industry accounting for one in every three containers handled in the world.
Decentriq, the “Switzerland of data”, enables effortless and secure data collaboration with Data Clean Rooms — neutral, dynamic compute environments for two or more parties to combine sensitive data and uncover new value. Designed for data scientists and business users, they give organizations a platform to harness a unique combination of privacy-enhancing technologies, such as Confidential Computing. It allows data to be “shared without sharing,” ensuring control, compliance, and unprecedented protection of proprietary data.
Decentriq’s clean rooms power data collaboration in the world’s most privacy and compliance-conscious industries, including media (Goldbach), healthcare (Roche), banking (PostFinance) and the public sector (Swiss Army). Decentriq is a founding member of the Confidential Computing Consortium alongside Microsoft, Google, Meta, and Intel.
Edelman for GSBN
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