Spotting suspicious activity faster (duration 5:19)
Next steps in the fight against financial crime
Banks have a key role to play in tackling serious crime. By reporting suspicious financial activity, banks help law enforcement agencies identify and prosecute criminals ranging from human traffickers to drug dealers.
HSBC takes these responsibilities very seriously. Over recent years we have taken a number of important steps to improve how we protect the integrity of the financial system – investing in new software, hiring experts, and changing the way we do business to better manage financial crime risk.
Staying one step ahead as threats to the financial system grow is a challenge, however. Criminals learn and adapt and international markets continue to become more interconnected and complex. These changes underline the limitations of the current approach taken not just in HSBC, but across our industry.
Estimates suggest that not even one per cent of criminal funds flowing through the international financial system are confiscated by law enforcement agencies. So it is time for all of us in the banking industry, and our partners, to rethink our collective approach.
Artificial intelligence could be a vital tool for pinpointing suspicious activity
HSBC intends to go further than current industry standard practice. We are aiming to significantly evolve our approach to financial crime risk management by using our size and scale to leverage all the data available to us and apply advanced analytical tools to it. Of course, like many banks we are already using analytics, and starting to implement artificial intelligence, to make the way we work now more effective. But, crucially, this is within the confines of the existing system.
The current approach taken across the banking industry to spot suspicious behaviour is to scan customers and transactions by analysing relatively limited sets of data. This might yield some useful insight, but there will always be limits to what can be learnt from a partial view of a very big picture.
Gathering together all of the relevant data held by a global bank, and bringing in external, publicly available data, will help us identify global patterns and systemic problems that might otherwise be invisible.
Making sense of the huge amount of information gathered in this way is a further challenge. As well as hiring experts, we are developing new analytical techniques, including by investing in cutting-edge software. Artificial intelligence that applies ‘machine learning’ can sift through vast quantities of transactions quickly and effectively. This could be a vital tool for pinpointing suspicious activity – helping us to deliver more timely, relevant and accurate information to law enforcement.
With technology developing at a rapid pace, we will need to learn fast and test new techniques over the coming years. And we will need to bring regulators and others with us on an evidence-based journey. I believe we have started on the right track, however – one that will make us faster, more responsive, and better able to protect the public we serve.