ENP Newswire -
Release date- 28082014 - Dr George Samakovitis Financial fraud knows no borders but regulatory bodies have no suitable global detection technology - that's the problem that has been tackled by academics led by the
They have developed prototype software to enable sensitive data to be shared between institutions, using artificial intelligence to so that their system teaches itself how to spot the latest scams.
Terrorism, piracy and drug trafficking are amongst the crimes that depend on money laundering. Banks and other financial institutions have long been using software to scan millions of transactions for any abnormalities that might indicate laundering. But, until now, such monitoring has largely been confined within the walls of each organisation because of confidentiality and competition.
Dr Samakovitis, pictured, Business Intelligence expert at the
'It gives a regulator like the
The more members or 'nodes' in the information-sharing network, the more powerful the system becomes. A participating bank will harness the collective intelligence of all participants in the network without having its data exposed to any other bank, and without other banks knowing how much fraud has happened within its walls: an example of 'network economics'.
George Samakovitis says: 'The scale of financial fraud today means banks and regulators need to share much more information than they do currently. Our proof-of-concept demonstrates that the technological solutions can be developed. What is now needed is wider consensus on a new regulatory framework. That is the principal missing ingredient in technology-assisted Anti-Money Laundering.'
The researchers are Dr Georgios Samakovitis from the Faculty of Architecture, Computing & Humanities,
To find out more about the way in which the university's researchers can help your business or organisation: http://enterprise.gre.ac.uk/
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