About the Customer

The customer is a large, globally operating industrial manufacturing company based in Europe, supplying high‑value equipment and technology to customers worldwide. As part of its international operations, the company manages a significant volume of trade finance instruments across multiple banks, regions and message formats. The organization operates in a complex banking environment where not all financial institutions are digitally connected through standardized networks.

Customer Challenge

The customer regularly receives Export Letters of Credit (LCs) and related amendments from its banks, but not all messages arrive through standardized SWIFT channels. In many cases, LC advices are delivered via alternative banking communication formats rather than SWIFT, limiting the ability to rely on predefined message mappings or automated bank integrations.

As a result, trade finance teams were required to manually read incoming messages, interpret the content and copy key data fields into their trade finance system. This process was time‑consuming, error‑prone and difficult to scale – especially when onboarding historical transactions during system migrations or handling growing transaction volumes.

Without addressing this challenge, the customer faced continued operational inefficiencies, limited scalability, increased risk of data inconsistencies and significant manual effort in both day‑to‑day operations and large‑scale deal migrations.

Partner Solution

Surecomp addressed this challenge by enabling AI‑driven document and message ingestion within its cloud‑native trade finance platform RIVO™, deployed entirely on AWS. The solution leverages Amazon Bedrock to access managed foundation models that can interpret unstructured trade finance messages and extract relevant deal data automatically.

Instead of building custom mappings for each non‑standard message format, the AI‑based ingestion capability processes incoming Export LC advices and amendments, identifies key trade finance fields and generates structured deal records directly within RIVO™. Users remain in full control, reviewing and validating extracted data before continuing with downstream workflows.

The solution runs on containerized microservices orchestrated by Amazon Elastic Kubernetes Service (EKS), ensuring scalability, resilience and secure integration with AWS services. All AI inference is performed via Amazon Bedrock, allowing the platform to benefit from managed model access, built‑in security controls and responsible AI guardrails without operational overhead.

This approach enabled the customer to handle both ongoing LC processing and large‑scale historical deal migration without lengthy development cycles or dependency on bank‑specific integrations.

Results and Benefits

The AI‑powered approach delivered measurable operational improvements:

  • Migration efficiency: More than 65 open Export LC deals and over 1,000 historical transactions were successfully migrated and archived using AI‑based ingestion.
  • Reduced manual effort: Trade finance teams significantly reduced copy‑and‑paste activity and manual data entry during both migration and daily processing.
  • Scalability: The solution enabled efficient handling of growing transaction volumes without increasing operational headcount.
  • Data alignment: Registered deal data remained consistently aligned with the content of incoming banking messages.

Early usage demonstrated that extraction accuracy improves as more examples are processed, with ongoing refinements further increasing reliability over time.

 

Surecomp is a global provider of cloud‑based trade and supply chain finance solutions for banks and corporates. Its flagship platform is built on AWS and combines secure, scalable infrastructure with embedded AI capabilities to automate complex trade finance workflows. Surecomp helps organizations reduce operational risk, improve efficiency and modernize trade finance operations using AWS‑native technologies.