Industry
Banking
Banking Services Transformation: Unlocking Exponential Value
Highlights
- Many banks have taken early steps by automating trade finance with cognitive solutions, but such efforts alone cannot unlock scale or long-term value.
- Generative AI and Agentic AI offer the next leap, enabling banks to move from task-based automation to intelligent, adaptive transformation.
- Sustained modernization will come from blending automation, cognitive intelligence, and regulatory compliance into a cohesive strategy.
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Foreword
Since pre-historic times, people have relied on trade, beginning with simple barter as the foundation of exchange. A few centuries later the silk road route was created to connect the trading partners. The journey from barter to silk road to the current digital world has been a revolutionary one.
There is a great dependency of global trade on trade finance instruments, which play a critical role in mitigating risks and facilitating payments for importers and exporters engaged in international trade.
Trade finance operations remain heavily paper-based, manually intensive, and subject to stringent regulations, making the process time-consuming and complex. These challenges have set in motion a wave of industry-wide transformation. An array of digital solutions is emerging to streamline operations and usher in a new era of digital trade. From our perspective, financial institutions must harness these digital levers—be it automation, analytics, or digitization—to stay competitive and relevant in an increasingly dynamic global market.
Digital Levers
GenAI and Agentic AI are driving a paradigm shift in trade finance, compelling banks and service providers to reimagine their operating models and product strategies. Key transformation levers include:
- Digitization and automation: AI-driven solutions are being piloted to streamline trade document verification, compliance checks, and customer service workflows.
- Disruptive technologies: Emerging technologies like Generative/Agentic AI are being explored for both traditional trade finance and supply chain finance applications.
- Regulatory evolution: The adoption of digital ICC frameworks such as eUCP and URDTT is facilitating more seamless and secure cross-border transactions.
AI in Trade Finance
Many banks have initiated automation in their trade finance operations using cognitive OCR solutions, but this approach alone falls short of unlocking the full potential and sustaining the pace of transformation. To truly modernize, banks must pivot toward GenAI and Agentic AI strategies that enable end-to-end transformation, integrating automation with cognitive intelligence and regulatory technology compliance.
The recommended approach involves deploying Human-in-the-Loop automation and adopting flexible AI architectures that support both Large Language Models (LLMs) and Small Language Models (SLMs). This shift empowers banks to address complex operational challenges with agility and intelligence.
Below are key use-cases where GenAI/Agentic AI can revolutionize trade finance back-office functions:
- Document checking: Automate letter of credit document checking with identifying and delivering the right discrepancies to stakeholders.
- Legal vetting: Bank Guarantees automation with identifying any discrepancies in the guarantee wording as per ICC/Legal laws.
- Compliance screening and AML Checks: Solutions have been built around highlighting red flags, disambiguation of screened data sets against the compliance filters.
- Dynamic pricing and sentiment prediction: Analytics shift from descriptive analytics to predictive/prescriptive analytics which helps the banks to forecast the future.
- Customer service: Chatbots and email automation is used for handling routine or even complex queries, providing real-time assistance across time zones and embedded in omnichannel platforms for seamless communication, affirmation, and allocation updates.
AI Benefits
GenAI and Agentic AI emerge not merely as technology enablers but as strategic differentiators in trade finance. Their implementation empowers banks to significantly reduce manual effort, reduce discrepancies/reject rate, accelerate turnaround times, enhance overall process efficiency and optimize operational costs.
These AI solutions also elevate customer experience, enable flexible adoption of new business models, and strengthen regulatory compliance frameworks.
Conclusion
While many GenAI and Agentic AI use-cases remain in early adoption, the greater challenge lies in seamlessly integrating these capabilities into existing ecosystems and reskilling or upskilling the current workforce to adapt. Success will hinge on choosing the right technology partners and working with trade finance experts who can tailor solutions to specific market needs and deliver them with speed and precision.