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74% of survey respondents wrongly assume banks use Artificial Intelligence to detect money laundering

New research by BAE Systems has found that 74% of business customers think banks use machine learning and artificial intelligence to spot money laundering. In reality banks rely on human investigators to manually sift through alerts – a hard-to-believe fact selected only by 31% of respondents. This lack of automation and modern processes is having a major impact on efficiency and expense when it comes to the fight against money laundering.

Brian Ferro, Global Compliance Solutions Product Manager at BAE Systems Applied Intelligence, said:

“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 By occupying key personnel with these manual tasks, banks are limiting the investigators’ role, impacting on their ability to stop criminal activity.”

Money laundering is known to fund and enable slavery, drug trafficking, terrorism, corruption and organised crime.  Three quarters (75%) of business customers surveyed see banks as central actors in the fight against money laundering. The penalty for failing to stop money laundering can be high for banks – and is not restricted to significant fines. 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.

Ferro continued:

“For banks to be on the front foot against money laundering, their investigators need to be supported by machine intelligence. Simplifying, optimising and automating the sorting of these alerts to give human investigators more time is the single most valuable thing banks and the compliance industry can do in the fight against money launderers. Right now, small improvements in efficiency of the systems banks use to find laundering can yield huge results.

“At BAE Systems we use a combination of intelligence-led advanced analytics to track criminals through the world’s financial networks. 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.”

About the research

The data contained in this release comes from 300 IT decision makers in the UK and the US, from organizations with 1000 employees or more, in a variety of commercial sectors. Interviews were conducted in February 2018, and were undertaken online using a rigorous multi-level screening process to ensure that only suitable candidates were given the opportunity to participate.

The research was conducted independently by Vanson Bourne, an independent specialist in market research for the technology sector. Their reputation for robust and credible research-based analysis is founded upon rigorous research principles and their ability to seek the opinions of senior decision makers across technical and business functions, in all business sectors and all major markets. For more information, visit www.vansonbourne.com.

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