What challenges did Hong Leong Bank face before AI implementation?

Slow, manual processing of high-volume trade documents such as invoices and shipping forms. Risk of errors and sanctions-screening delays in trade operations and underwriting. Need to improve customer and employee experiences while preserving data governance and security.

What was the impact of the AI solution?

Document AI delivered a 30% efficiency gain in trade operations by removing manual entry and human errors. The Marina chatbot handled 70% of chat volume. Chatbot accuracy improved from 75% to 99%. Monthly chat transactions increased 3x.

Rank#351of 3,107

Source

GCP

Hong Leong Bank accelerates trade finance document processing with Document AI and deploys Gemini agents on Vertex AI

Use case typeCustomer support automationUpdated Jun 13, 2026

Hong Leong Bank (HLB) built its AI ecosystem on Google Cloud to improve digital banking and employee experiences. The bank uses Document AI for trade operations to automatically extract and digitize relevant fields from high-volume trade documents in more than 200 languages. HLB also runs Gemini 2.5 Flash as a private instance on Vertex AI and uses Agent Development Kit-based agents for customer and internal workflows.

Organization: Hong Leong Bank
Industry: Finance
Location: Malaysia
Published: June 2026

Reported outcomes

monthly chat transactionsCustomer experience

+30%efficiency gain in trade operations+99%chatbot accuracy+70%chat volume handled by chatbot

Strategic outcomes

Risk & complianceImproved sanctions screening and document accuracyCustomer experience & trustImproved customer and employee experiencesNew product / capabilityDeployed private AI chatbot agentsScale & capacityHandled high-volume chat interactions

Catalog median for customer experience deployments: +69% across 99 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 3

1Trade Finance Automation
2Customer Service Automation
3Employee Productivity

Slow, manual processing of high-volume trade documents such as invoices and shipping forms.
Risk of errors and sanctions-screening delays in trade operations and underwriting.
Need to improve customer and employee experiences while preserving data governance and security.

Built an AI ecosystem on Google Cloud centered on Vertex AI and Document AI.
Used Document AI Trade Operations OCR to extract and classify document fields and support sanction screening.
Deployed Gemini 2.5 Flash as a private instance on Vertex AI for chatbot and agent workflows.
Used the Agent Development Kit and secure API calls to connect Gemini agents to backend systems.
Added Cloud Run, Cloud SQL, Google Cloud Search, Compute Engine, and Gemini Code Assist as supporting services.

Technologies

Google Cloud Document AI Vertex AI Gemini 2.5 Flash Agent Development Kit Cloud Run Cloud SQL Google Cloud Search Compute Engine Gemini Code Assist

Document AI delivered a 30% efficiency gain in trade operations by removing manual entry and human errors.
The Marina chatbot handled 70% of chat volume.
Chatbot accuracy improved from 75% to 99%.
Monthly chat transactions increased 3x.

Implementation partners1

Cloud Space

Sources & evidence1

Groundedness: 5/5Type: Customer StoryPublished: Jun 7, 2026Publisher: Google CloudEvidence: VendorConfidence: Medium

Primary source

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Customer evidence