HSBC deploys algorithms to fight financial crime

money laundering

Says its automated anti-money laundering system is an industry first

by Max Smolaks 27 September 2019

Banking giant HSBC’s trade finance business has introduced an automated financial crime detection system that can identify more than 50 potential money laundering scenarios.

The bank calls the system, built in partnership with British startup Qantexa, an industry first.

It already screens all trade finance transactions in the UK and Hong Kong and is being rolled out worldwide.

The business has also introduced an automated sanctions checking system, developed in-house using machine learning technologies. It is live in India and will be deployed across 41 markets by the end of the year.

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

“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.”

HSBC’s GTRF business is essentially the world’s largest trade finance bank, processing $1 million worth of trade turnover every minute. It has customers in 56 countries, and screens over 5.8 million transactions a year for signs of money laundering and other financial crime.

Qantexa is an analytics and AI startup established in London in 2016. A big chunk of its funding comes from HSBC, which participated in two out of three funding rounds to date.

Qantexa created a system that relies on automated ‘contextual monitoring’ to build a financial transaction profile that draws on both internal and external data – for example, company ownership information. The automated system then uses algorithms to identify suspicious patterns and common signs of criminal networks.

Its creators say the system at HSBC makes more than double the average number of checks against indicators at a transactional level.

“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,” explained Vishal Marria, CEO of Quantexa.