Artificial Intelligence (AI) is transitioning from a buzzword to a transformative force in trade finance, as banks explore its potential to enhance data management, risk assessment, and client services. In a recent roundtable discussion, experts from Barclays and EY delved into the implications of agentic AI, highlighting its capacity to streamline document workflows, bolster fraud detection, and redirect focus towards genuine risks while nurturing client relationships.
Participants in the roundtable included James Sankey, partner at EY; Jaya Vohra, global head of trade and working capital at Barclays; Chris Withers, AI transformation leader at EY; Steve Wright, chief information officer at Barclays; and moderator Shannon Manders of GTR.
As AI continues to redefine financial services through automation and enhanced client insights, a pivotal question arises: are we moving beyond experimental pilots to realize tangible value? Withers noted that AI is evolving from being technology-driven to business-driven, with significant strides made in the last nine months. He emphasized a shift from “assist-me” tools, such as Microsoft Copilot, to more integrated AI solutions that act as digital teammates within existing workflows.
The embedding of AI into processes promises substantial opportunities, including improved customer experiences, new revenue streams, and increased operational efficiency. However, it demands a fundamental rethinking of processes and the roles of personnel, requiring domain experts to ensure effective integration of AI agents.
Wright further highlighted the challenges associated with viral adoption in trade technologies, noting that with AI, the barrier to entry is less pronounced. This capability allows organizations to implement AI solutions more rapidly. Barclays is currently leveraging “assist-me” tools, though adoption remains dependent on changing user habits.
Vohra pointed out that while the industry is still in early phases—approximately six to nine months into exploring agentic AI—there is notable excitement surrounding its potential to facilitate a frictionless customer experience and streamline global trade processes. She posited that AI could bridge gaps in legal frameworks and interoperability, enhancing document management beyond traditional methods.
“The whole digital trade journey has relied on legal frameworks and interoperability, and I do wonder whether AI could be that missing piece to accelerate it.”
Jaya Vohra, Barclays
The discourse transitioned to the significance of data integrity in trade finance, a challenge that persists in the industry. Wright stated that while advancements have been made in converting physical documents to structured data, the next hurdle lies in determining which data sources can enhance AI’s effectiveness. Quality data is crucial for accurate outputs and informed decision-making.
Sankey emphasized that document interpretation stands out as a prime use case for AI in trade, given the manual, document-heavy nature of transactions. He noted the potential for large trade banks to leverage their unique data sets to offer clients tailored insights, further enhancing the value proposition of banking relationships.
As AI evolves, its applications are also extending into risk management and compliance. Sankey reported that AI is aiding Know Your Customer (KYC) processes by automating data collection and onboarding, as well as enhancing transaction monitoring to identify unusual patterns. However, he cautioned that most innovations remain in pilot stages, as data integrity issues continue to pose challenges in compliance contexts.
Vohra highlighted the need for AI to support human judgment rather than replace it, especially in critical areas like trade-based money laundering. She envisions a future where AI-generated insights require human validation before implementation, thereby enhancing risk management practices.
“AI is going to be transformational, and there’s huge interest from engineers and teams across the bank, but we still have a business to run today, with existing technology and priorities that don’t involve AI.”
Steve Wright, Barclays
Regarding governance, Wright stressed the importance of involving risk and control teams early in the development of AI applications to ensure that compliance measures are integrated from the outset. Adapting existing governance frameworks to accommodate the rapid advancements in AI without stifling innovation is crucial.
As financial institutions prepare for the future, Sankey noted the evolving role of treasurers and trade financiers in an AI-driven environment. With treasurers increasingly seeking AI solutions to manage liquidity and optimize returns, the demand for tools that provide real-time insights and strategic advice will only grow. Vohra echoed this sentiment, emphasizing the importance of using data analytics to guide clients toward informed decisions.
In conclusion, as banks navigate the complexities of AI integration, the focus will be on developing efficient, transparent systems that enhance operational capabilities while maintaining the human element essential for nuanced decision-making. With the advent of agentic AI, a new chapter in trade finance is unfolding, potentially reshaping the industry’s landscape.
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