After receiving a $1.9bn (£1.2bn) fine over money laundering in 2012, HSBC admitted that its money laundering controls were not fit for purpose. The bank said back in 2017 that it is using Google Cloud machine learning capabilities for anti-money laundering.
The CIO at HSBC Darryl West said the bank is using machine learning to run "analytics over this huge dataset with great compute capability to identify patterns in the data to bring out what looks like nefarious activity within our customer base. The patterns that we identify are then escalated to the agencies and we work with them to track down the bad guys."
Read next: HSBC turns to Google Cloud for analytics and machine learning capabilties
HSBC has also been working with the London-based big data startup Quantexa to help the bank spot potential money laundering activity.
HSBC has been piloting the technology since 2017, which uses AI techniques to analyse internal, publicly available, and transactional data within a customer’s wider network to spot rogue behaviour. It is now integrating Quantexa technology into its systems this year.
The bank participated in a $3.3 million (£2.3 million) funding round in Quantexa in March 2017.
Ray O’Brien, HSBC’s global risk COO and head of global risk analytics, said: “Following our investment in Quantexa, we are looking forward to working closely with the company to utilise its technologies as we become more intelligence led in our approach to financial crime risk management.”
As startups like the UK-based ComplyAdvantage try to show, AI is ripe for application to tracking money laundering as it is especially good at spotting odd behaviour within large data sets, like banking transactions.