New research by BAE Systems has found that 74% of business customers think banks use machine learning and artificial intelligence to spot money laundering, but in reality human investigators are manually sifting through alerts, said a recent survey from BAE Systems.
Compliance investigators at banks can spend up to three days of their working week dealing with alerts – which most of the time are false positives, said Brian Ferro, a product manager at BAE Systems’ applied intelligence unit, in a statement.
Having to deal with these manual tasks means banks are limiting the investigators’ role, impacting on their ability to stop criminal activity, he added.
75% of business customers surveyed see banks as central actors in the fight against money laundering, which is is known to fund and enable slavery, drug trafficking, terrorism, corruption and organized crime.
The penalty for failing to stop money laundering can be high for banks – and is not restricted to significant fines. There are also high costs to reputational risk.
When questioned, 26% of survey respondents said they would move their business’ banking away from a bank that had been found guilty and fined for serious and sustained money laundering that it had not identified.
Investigators need to be supported by machine intelligence, said Ferro: “By putting machine learning and artificial intelligence systems to work to narrow down the number of alerts, human investigators can concentrate on tasks more suited to their talents and insight.”