The Industry Landscape
The Need to Advance Trade Finance Through AI-led Intelligent Operations
Trade finance remains one of the most operationally intensive functions, defined by fragmented workflows, multiple processing systems and increasing compliance obligations.
As volumes grow and customer demands evolve, leading banks are exploring AI in trade finance, blending intelligent automation, workflow orchestration and invaluable human input. This enhances productivity, speeds up transactions and fortifies operational control.
The Client Challenge
Fragmented Workflows | Manual Trade Processing
The client was keen to transform its end-to-end trade finance operations encompassing the Letter of Credit (LC), Letter of Guarantee (LG), Open Account Financing (OAF), and Structured Deals and Collections. Existing operations relied heavily on fragmented processes, conventional Business Process Management Systems (BPMS), discrete systems such as FSK and PurpleTRAC, and traditional ways of working, resulting in operational complexity, higher costs and slower execution.
The Solution
An AI Agent-led Operating Model for Intelligent Trade Finance Operations
WNS collaborated with the client to re-design trade finance operations by introducing an AI agent-led operating model that combined intelligent execution, Appian-powered workflow orchestration and human expertise.
The transformation re-shaped how work is performed throughout the trade finance lifecycle, enabling AI agents to execute routine tasks. At the same time, automation streamlined supporting processes and human expertise remained focused on exceptions and critical business decisions.
The Outcome
Higher Productivity | Faster Execution | Stronger Operational Control
The transformation re-defined trade finance operations through a best-in-class operating model that improved productivity, accelerated processing and strengthened governance. By optimizing the maker's role and reducing operational complexity, the client established a more scalable, efficient and customer-centric trade finance function.
Tangible outcomes included:
60–70percent
improvement in productivity
30percent
reduction in turnaround time
>85percent
Customer Satisfaction (CSAT)
50percent
reduction in compliance-related handoffs
FAQs
1. How can AI improve trade finance operations?
AI can take on routine trade finance activities, reduce manual effort, and accelerate processing. Combined with workflow orchestration and human expertise, it can also improve consistency, strengthen operational control, and enable operations to scale more effectively.
2. What are AI agents in trade finance?
AI agents can execute defined trade finance activities that would traditionally require manual intervention. In this engagement, AI agents handled routine maker activities, while human experts focused on exceptions, fallouts, and critical business decisions.
3. How does trade finance automation reduce processing time?
Automation reduces repetitive manual activities and handoffs across trade finance workflows. Here, AI agents and Appian-powered workflow orchestration streamlined execution and supporting processes, contributing to a 30 percent reduction in turnaround time.
4. What role does human expertise play in AI-led trade finance operations?
Human expertise remains critical for activities requiring judgment and oversight. The operating model enabled AI agents to handle routine work while people focused on exceptions, operational fallouts, and key business decisions.
5. What are the benefits of an AI agent-led trade finance operating model?
An AI agent-led model can improve productivity, accelerate turnaround times, reduce manual and compliance-related handoffs, and strengthen operational control. For this bank, the transformation delivered 60–70 percent higher productivity, a percent reduction in turnaround time, and a 50 percent reduction in compliance-related handoffs.