As technology improves, is it possible that online financial crime and fraud will subside into historical events that companies will learn from?
HSBC is incorporating Artificial Intelligence (AI) to tackle money laundering and notably the SFO recently used a pilot ‘robot’ in the Rolls-Royce investigations to process more than half a million documents a day scanning for legal professional privilege content at speeds 2,000 times faster than a human lawyer.
If AI is the modern solution to combat the challenges of money laundering and huge volumes of disclosure, conventional methods may become a thing of the past.
Traditionally, the finance industry has relied heavily on manual, repetitive ways to stop money laundering and since online banking has been alive, even with the development of complex algorithms to try to combat fraud, money laundering problem only grew.
HSBC’s initiate to employ AI to prevent fraud, terrorist funding and the unlawful transfer of money from one account to another. Its solution is thought to be fast and cost-efficient; integrating smart software that screens customers’ financial data at top speeds, identifying any suspicious behaviour on the way.
With an increasing number of companies being subject to fines for failing to prevent money laundering including the most recent case of Paddy Power and William Hill being fined, banks and businesses are keen to incorporate AI in an attempt to avoid billion pound fines.
HSBC has now invested billions into improving its compliance controls, following the billion pound settlement in 2012 to avoid charges for breaching US sanctions on countries such as Sudan and Iran.
The new software cleverly scans data from addresses, telephone numbers, company director names and news, Its software scans structured and unstructured data on transactions from different sources, such as phone numbers, addresses and company directors.
Royal Bank of Scotland has also invested in similar initiatives to spot fake invoices and attempted fraud, by scanning its small business clients’ transactions.
For disclosure mountains, terabytes of computer information can be reviewed quickly and AI can spot connections far more quickly than humans can. AI can assist tracking communications and interactions between parties to build a network web to determine the relevance (or not) of key individuals and entities under investigation. This would otherwise take hundreds of hours at enormous cost. The benefits should reflect a more fair and reliable disclosure process and a more streamlined, efficient and reliable product, in addition to cutting delays for detection, investigation and prosecution of crime.
As always, anything involving robots and AI will spark debate on the efficiency of such technologies and potential errors, as well as replacing human judgement and emotional intelligence. Any company trialling AI software, needs to carefully examine and weigh the capabilities with the risks. Building trust in AI solutions is still in the primary stage.
The fight against money laundering will remain for decades, until new technologies and resources can block all online money laundering. AI is still in it’s early stages and can only improve itself whilst keeping up pace with money laundering experts out there. AI’s learning capability combined with skilled investigators can prove to be an effective model for compliance control.
How do you train a robot to adhere to data protection policies and use of personal data, whilst controlling what information it shares and how. There are numerous risks and varying levels of complexity in all directions that must be carefully maintained in the rollout of AI especially in banks. But for now, companies have no other choice but to adopt AI software to avoid fines for failing to prevent money laundering.
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