MDBs: Advancing development through trade
Alexander Malaket
Apr 18, 2025
Carter Hoffman
Apr 10, 2025
At Finastra’s Europe Corporate Banking Day, held in London on 26 March 2025, banking and technology executives from across the trade space discussed many of the trends that they see as shaping the industry in the years to come.
From artificial intelligence trends to talent shifts, the core message from the event, if you had to boil it down to just one, would be that change – in its many different forms – is the name of the game.
And that change starts with the broader context within which trade finance operates.
The lending dynamics in trade finance are shifting. As borrowers look for optimal financing options, there has been a growing appetite for direct lending, which is being increasingly satiated by institutional investors and private credit entities.
Externally, thanks in part to global political and economic fluctuations, new trade corridors are starting to emerge that are shaping how goods physically move from one side of the world to another.
Amid all these changes, firms are looking to mitigate the potential risk associated with the ensuing uncertainties by tightening their liquidity management. Practically speaking, this is manifesting in a noticeable shift from payables to receivables financing.
While this adjustment in the types of financial solutions being used can present several challenges, including operational inefficiencies and regulatory compliance, it also presents a large opportunity for those willing to embrace the change and lean into the needed innovation.
One of the leading sources of this innovation today is digitalisation.
During an audience poll at the Finastra Europe Corporate Banking Day, 44% of institutions identified digitalisation as both their greatest challenge and their greatest opportunity.
Given the current situation, that should come as little surprise.
Today, corporations of all sizes demand personalised, digital, and instant banking services, regardless of whether these occur locally or across the globe. Banks, in response, have an opportunity to capitalise on this desire by building customer-centric digital journeys that help clients achieve their business needs.
Banks, too, have a massive opportunity to enhance their internal operations through digitalisation. By investing in straight-through processing (STP) and leveraging automation to reduce loan approval times, banks would mitigate the administrative bottleneck in their lending operations and make banking more accessible to all.
The challenge is that this is still a really hard thing to do, even with the improvements in technology this century. A vast proportion of data still exists in paper form or in disparate siloes, which makes it unpalatable to digital systems. With concerted efforts and the help of the latest advancements banks should be able to make incremental improvements to reducing this.
As it stands, some of the key technologies helping to bring about widespread digitisation include cloud computing, microservices, application programming interfaces (APIs), digital ecosystems, and artificial intelligence (AI).
Banks aren’t immune to the AI wave that has swept the globe since OpenAI released the first commercial version of ChatGPT in November 2022. Increasingly, AL tools, in their various forms, are being integrated into a number of banking operations, helping to power up the humans who are operating in these roles.
The benefits are no longer purely theoretical. JPMorgan Chase, for example, has reported a 20% increase in software engineers’ efficiency due to an AI coding assistant, allowing more focus on high-value projects, according to a New York Post report. The Commonwealth Bank of Australia (CBA) has also established a tech hub in Seattle to enhance AI skills with the aim of strengthening Australia’s AI capabilities.
For more administrative tasks, the benefits of AI seem clear-cut. It can accelerate document processing, compliance checking, and contract approval times, helping with operational efficiency and allowing more businesses, particularly smaller ones, to have a stronger chance of accessing much-needed financing.
Large Language Models (LLM), the version of AI that uses machine learning to understand, interpret, and generate human language, are also claimed by many to be bridging the knowledge gap by making previously opaque information more accessible to all employees. Perhaps this is the case, but it may not be enough to address a growing talent gap.
What happens when the cohort of trade finance veterans with decades of experience and accumulated intuition retire? In theory, their proteges will step into the role, themselves being replaced by a new batch of younger talent.
Many institutions, however, are struggling to find this new, young batch. Nearly a quarter (24%) of respondents to Finastra’s audience poll reported that talent attraction and retention were the biggest challenges they faced.
In its current state, trade finance is a far cry from the glamorous fields that eager new graduates aspire to work in. To address this, administrative roles must be migrated, upskilled, and digitised to attract and retain younger talent. Beyond hiring, there is a pressing need to capture and transfer their knowledge to the next generation, perhaps by increased investment in education or through mentorship schemes to facilitate knowledge transfer.
With a changing backdrop, changing technology, and changing faces, those operating in the trade finance space need to be prepared to embrace change.
With digitisation and AI presenting both challenges and opportunities, financial institutions must proactively invest in digital technologies, integrate AI into their operations, and develop strategies to attract and retain talent.
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