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Predictive analytics in fraud and AML
Journal of Financial Compliance,
1
(1),
17-26
(2017)
Abstract
The common problem we are all facing in fraud risk and compliance these days is how to address the challenge of reducing false positive rates to optimise detection for fraud and, very importantly when monitoring transactions for anti-money laundering/ counter-terrorist financing (AML/CTF), how to avoid being overwhelmed by alerts. This paper aims to introduce to the reader the importance of considering the use of predictive analytics in the financial crimes prevention strategy and programme of any organisation. This paper starts by offering a detailed background of the scope of the fraud and AML/CTF problem in general, focusing on the high costs that many organisations face when trying to prevent and detect financial crimes and also protect their genuine customers from becoming victims of financial crimes. The paper goes on to describe the most common challenges that organisations face, in particular resource challenges when devising and implementing their strategies. It also encourages a collaborative approach to fraud prevention. The reader can expect to gain insightful information about how predictive analytics can be used in the prevention of financial crimes and what type of benefits it can deliver.
Keywords: predictive; model; detection; false positive; prevention; victim
The full article is available to subscribers to the journal.
Author's Biography
Clinton Mills has more than 25 years’ experience in the use of technology to manage consumer and small business fraud and credit risk and compliance throughout the Asia Pacific, Middle East, African and European regions. He has worked with many banks and other financial services companies globally to implement solutions to prevent fraud and manage risk and compliance. Clinton has been the Managing Director of GBG DecTech for 15 years, a Microsoft Gold qualified partner in application development with Silver in data analytics and data platform. Clinton reports to the Group Managing Director of GBG, an identity data intelligence company listed on the London Stock Exchange that helps organisations make decisions about the customers they serve and the people they employ.
