Criminals are hiding in
plain sight

Traditional monitoring systems can’t handle the scale

Existing transaction monitoring systems produce thousands of false positives so your team has to manually process paperwork to uncover real risk.


Money laundering fuels horrendous crimes

Trade-based money laundering is more than evading import duties or currency restrictions. It’s used to move corrupt funds, enable human and wildlife trafficking, and smuggle weapons.


You need to bridge across financed, open account trade products and normal payments

You might be able to see more in financed trade, but the manual processes are time consuming. And with non-financed trade, you have huge information gaps.

How to effectively detect trade-based money laundering and financial crime using an automated contextual approach to data

Uncover hidden connections in seconds

Global trade is made up of complex relationships and behaviors between importers and exporters. To manage risk effectively and efficiently, you need to understand the context of their businesses, ownership structures, geographies and where they sit in broader supply chains.


By connecting multiple internal and external data sources, you can see the complete picture of your customers and their counterparties. So your teams can reveal hidden risks and make faster, more accurate decisions about potentially suspicious activity, without being overrun by false positives.


Contextual Decision Intelligence changes the way everyone makes decisions.

Find out why

reduction in false positives
SAR escalation rate

Improve trade-based money laundering detection with context


Manage the complexity and global scale of trade using contextual monitoring to enhance risk detection from a single platform.




Combine data
to create context

Combine billions of internal and external data records to create a holistic view of transactional, customer, and counterparty information.


Add context to
trade relationships

See importer and exporter relationships to understand who they are, where they are, their size, who else they trade with, and where they sit within the supply chain.


criminal behavior

Stop trade-based money laundering before it happens, mitigate risk, and detect suspicious behavior pre-trade rather than post-trade using advanced network analytics.

Use the platform for Contextual Decision Intelligence

Learn more

The introduction of the first automated AML capability in the Trade Finance industry enables HSBC to more effectively concentrate our resources on genuine financial crime risk within our business and make trade safer for customers and society. Adrian Rigby, COO of GTRF, HSBC

Benefits of our Trade AML solution

Context is critical in the detection of trade-based money laundering. Our approach provides more accurate and efficient detection so you can decrease losses, protect your reputation, and increase the quality of alerts while reducing the volume.


Tailored for trade

Manage risk in the complexity and scale of trade across financed and open account transactions.

Reduce manual checks

Rely on data, analytical models and software to automate manual controls.

Reduce false positives 

Manage and reduce costs by focusing on the real risk and suspicious behaviors.

Become self-sufficient

Certified staff can change parameters and create new scenarios.

OCR and digitized data is not required

Use the data already available within your organization.

Apply solution to detect fraud

Tackle trade finance fraud using the same platform and data.

Make trade safer

Combine human expertise with advanced analytics to understand and detect criminal typologies.

Create a dynamic single view

See a complete picture of your customer, including size, geography and supply chain.

HSBC enhances financial crime detection with an industry-first automated trade AML system

HSBC Global Trade and Receivables Finance (GTRF) business wanted to improve the effectiveness of its AML monitoring to better combat financial crime.


Quantexa’s contextual approach enables the bank to better identify suspicious patterns and potential criminal networks by combining customer and counterparty trade information, transactional data and external insights.


Our technology automatically screens more than 5.8 million trade finance transactions each year against over 50 different scenarios that indicate signs of money laundering. This is double the average number of checks against indicators at a transaction-level.


Read the case study

HSBC AML case study

How to effectively tackle trade-based money laundering

Find out how an automated trade AML solution—using contextual monitoring—helps consistently and effectively detect money launderers and prevent financial crime.


Download now

Trade-based money laundering ebook

Why use the Quantexa platform

Build Once, Use Many, Ingest to Create a Single View with Networks

Apply your data to multiple use cases—without replicating data sets.

Make Faster, More Accurate Decisions

Use context to improve decision accuracy across the organization, find new opportunities and uncover risk.

Scale to Billions of Records in Batch or Real-time

Built on proven, scalable open-source technologies like Hadoop, Spark and Elastic.

Future-proofed Open Architecture

Integrate seamlessly into your existing IT ecosystem, with flexible deployment options: native, or containerized for private and public cloud.

Ensure Data Transparency

Use explainable data linking, advanced AI and decision models for regulatory compliance.

Keep Data Secure

Rely on granular security levels for dynamic control, with all activity audited.

Speedy Time-to-value

Operationalize your data in a matter of months – not years.

Overcome Data
Quality Issues

Use entity resolution and data volume to overcome missing or poor quality data.

Get the latest thinking, advice and opinions

Book a demo

See how our Contextual Decision Intelligence platform improves the effectiveness of operational investigations, speeds up complex investigations, and detects previously hidden risks.

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