HSBC introduces industry leading financial crime detection systems

HSBC Global Trade and Receivables Finance (GTRF) business has deployed an industry-leading Anti-Money Laundering (AML) system and an automated sanctions checking system as part of its ongoing efforts to improve financial crime detection.

In an industry first, the new customer surveillance system uses big data, advanced analytics and automated ‘contextual monitoring’ to detect and disrupt financial crime in international trade. The contextual approach, developed with Quantexa, builds on HSBC’s expertise in network analytics to enable the bank to better identify suspicious patterns and potential criminal networks by combining customer and counterparty trade information, transactional data and external insights. It is currently active in the UK and Hong Kong and is being rolled out across HSBC’s global network.

Adrian Rigby, COO of GTRF at HSBC, said: “This new capability marks a significant milestone in the bank’s intelligence-led approach to detecting financial crime. 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”.

The new system combines bank data and external data, such as company ownership information, to identify links between counterparties and transactions and map out networks. It automatically screens all trade finance transactions against over 50 different scenarios that indicate signs of money laundering, such as associated networks and payment patterns. This is more than double the average number of checks against indicators at a transactional level. It also provides investigators with an enhanced ability to analyse counterparty activities and relationships to better identify potential financial crime.

Vishal Marria, CEO of Quantexa, added: “The solution built with the Quantexa platform uses billions of data points to provide an entity resolution and network intelligence framework which references over 40 billion financial transactions. Using this technology, customer activities can be continuously assessed and scored for risk. This level of contextual monitoring improves accuracy, and decision making, while providing insight into data relationships never before possible.”

As the world’s largest trade finance bank, HSBC screens over 5.8 million trade transactions a year for signs of money laundering and other financial crime. One of the key challenges in detecting financial crime is establishing where people or companies are acting together to move money around the globe. Now, if there are concerns about the activities of a counterparty, a financial crime investigator can rapidly build a detailed picture of the links and transactions within a customer’s global network and identify previously unknown details.

Coinciding with the new AML surveillance launch, HSBC has automated first line sanctions checking using advanced algorithms and machine learning technology. Automated sanctions checking is now live in India and will be deployed in 41 markets by year end.

The automated solution, developed in-house, produces an instant response. By removing manual checks it reduces the processing time for each search and significantly eliminates false positives. Since HSBC initiates around one million sanctions screening submissions a month, this significantly improves the bank’s control environment as well as improving transaction speed for clients.

Collectively, these innovations will help HSBC to fight financial crime through accurately identifying criminal activity and networks that might not have been possible previously, ultimately helping to protect customers and their communities from financial crime.

Author: Yash Hirani

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