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Building Intelligent Trade Finance Operations for a Middle Eastern Bank

Read | Aug 27, 2026

AUTHOR(s)

A WNS Perspective

Key Points

  • A Middle Eastern bank was looking to move away from manual, document-intensive trade finance operations, where repetitive data entry, re-work and multiple compliance interventions were slowing processing and making it difficult to scale.
  • WNS introduced an intelligent trade-processing framework, combining AI-powered document extraction, human-in-the-loop validation and intelligent data enrichment. This created an integrated workflow from document ingestion and validation through to automated data population in the bank’s trade finance system.
  • The new model established a foundation for more standardized, accurate and scalable trade finance operations, with the potential to extend intelligence further into document checking, FOL processing and advanced TBML detection.

The Industry Landscape
Modernizing Trade Finance Operations in a Document-intensive Banking Environment

Trade finance is one of the most operationally intensive functions within commercial banking. Every Import or Export Letter of Credit (LC), Letter of Guarantee (LG) and documentary trade transaction requires large volumes of information to be extracted, validated, entered into multiple systems and reviewed against stringent compliance requirements.

While many banks have invested in trade finance automation and the digitization of individual activities, operations often still rely on manual document processing, fragmented workflows and repetitive data entry.

As transaction volumes continue to increase alongside heightened regulatory scrutiny, financial institutions are looking beyond automation toward intelligent trade operations that combine AI, workflow orchestration and human expertise to improve processing efficiency, strengthen compliance and support scalable growth.

The Client Challenge
Manual Processing | High Error Rates | Compliance Bottlenecks | Limited Scalability

The client's trade finance operations relied extensively on manual processing across Import LCs, Export LCs, LGs and related trade instruments. Associates manually downloaded documents, allocated transactions and entered 30+ transaction fields into the trade finance platform for every case.

Changing Customer Expectations

Document Processing & Data Capture

  • Manual download, allocation and indexing of trade documents
  • Repetitive entry of 30+ transaction fields for every trade instrument
  • Heavy dependence on PDF- and image-based document processing
  • Significant operational effort across high transaction volumes
Changing Customer Expectations

Processing Accuracy & Operational Efficiency

  • First-pass error rates averaging 5-6 percent for certain document types
  • High levels of manual validation and re-work
  • Longer transaction processing cycles
  • Operational resources focused on repetitive administrative activities rather than higher-value work
Changing Customer Expectations

Compliance Processing

  • Manual routing of transactions for name / sanctions and vessel screening
  • Compliance reviews and referrals creating processing bottlenecks
  • Additional effort required for TBML validation
  • Multiple manual intervention points across compliance workflows

Collectively, these challenges increased operational effort, limited processing scalability and constrained the client's ability to improve turnaround times while maintaining strong compliance controls.

The Solution
Intelligent Trade Finance Operations | AI-powered Document Processing | Workflow Orchestration

WNS partnered with the client to modernize trade finance document processing by implementing an intelligent processing framework that combines AI-powered document extraction, Human-in-the-Loop (HITL) validation and intelligent data enrichment for downstream compliance processing.

Powering the framework was WNS’ proprietary SKENSE IDP platform, combined with Microsoft Power Automate to create an integrated ecosystem that eliminated manual data entry, reduced processing time and prevented compliance penalties.

How Intelligent Trade Processing Works

The Client Challenge - 8 Finance Workstreams
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1. AI-powered Trade Finance Document Processing

  • SKENSE automatically retrieves Import and Export LCs, LGs and other trade documents.
  • Leveraging intelligent document processing and machine learning, SKENSE identifies and extracts the required transaction data from structured and unstructured documents.
AI-powered Trade Finance Document Processing

2. HITL Validation

  • The extracted information is presented to operations teams through a HITL validation layer.
  • Associates review the extracted data, validate system-generated warnings and correct exceptions where required, ensuring high levels of accuracy before the transaction progresses to downstream systems.
HITL Validation

3. Intelligent Data Enrichment

  • Once the transaction data is validated, Microsoft Power Automate bots seamlessly take over, automatically populating the required 30+ transaction fields directly into the client's TI+ trade finance system for all applicable trade products.
Intelligent Data Enrichment

The Outcome
Faster Processing | Higher Accuracy | Stronger Operational Efficiency

The transformation is expected to deliver measurable improvements across trade finance processing by reducing manual effort, improving transaction accuracy and strengthening compliance workflows.

 
Processing Efficiency

Processing
Efficiency

  • Designed to process more than 1.1 million trade finance document pages annually
  • Estimated operational benefits, leading to 15-20 percent capacity released
  • 3-5 percent improvement in trade-processing turnaround time
Processing Accuracy

Processing
Accuracy

  • 3-4 percent improvement in first-pass accuracy rates
  • Machine learning models targeted to achieve approximately 95 percent document extraction accuracy
Operational Transformation

Operational
Transformation

  • Standardized and automated trade document-processing workflows
  • Improved scalability to support growing trade volumes
  • Stronger governance through integrated HITL validation

Building on the success of Phase 1, WNS and the client have identified additional opportunities to extend the solution and further strengthen operational efficiency, compliance and scalability, creating future-ready trade finance operations.

WHAT'S NEXT
Extending Intelligent Trade Finance Operations

The Client Challenge - 8 Finance Workstreams
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FAQs

1. What are intelligent trade finance operations?

Intelligent trade finance operations combine AI, automation, workflow orchestration, and human expertise to streamline document-intensive processes, reduce manual intervention, and improve accuracy, compliance, and scalability.

2. How can AI automate trade finance document processing?

AI-powered Intelligent Document Processing (IDP) can automatically retrieve trade documents and extract required transaction data from structured and unstructured formats. In this engagement, WNS SKENSE IDP used machine learning to extract information from Import and Export LCs, LGs, and other trade documents, reducing the need for manual data capture.

3. How does human-in-the-loop validation improve trade finance processing?

Human-in-the-Loop (HITL) validation combines automation with human oversight. Operations teams can review AI-extracted data, validate system-generated warnings, and correct exceptions before information moves to downstream systems, helping maintain accuracy and governance while reducing manual effort.

4. What benefits can banks achieve from trade finance automation?

Trade finance automation can help banks reduce manual effort and re-work, improve processing accuracy and turnaround times, strengthen compliance workflows, and create greater capacity to handle growing transaction volumes. It can also provide a more standardized and scalable foundation for trade finance operations.

5. What technologies were used to modernize the bank's trade finance operations?

The solution combined WNS SKENSE IDP for AI-powered document extraction, a Human-in-the-Loop validation layer for review and exception handling, and Microsoft Power Automate to populate validated transaction data automatically into the bank's TI+ trade finance system.