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Financial crime needs a new approach

Lachlan Maddock
— 1 minute read

Financial crime costs the global economy as much as $1.45 trillion a year, while institutions lag on tech and expertise.

Financial institutions, rich in personal and financial data, present a lucrative target for criminals. Lack of expertise and legacy IT systems compound the threat posed by criminals, whose skills and capabilities are often light-years ahead of those of the institutions in their crosshairs.

“Traditional financial crime platforms have a limiting effect on our capability to combat financial crime,” Dr Richard Harmon, financial services managing director at Cloudera, told Investor Daily. 

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“Much of this comes from the siloed infrastructure that many institutions currently have in place. This results in a rigid data and technology environment that [require] frequent, costly and complex retrofitting of applications in order for those platforms to counter new crime patterns.”

“As a result, many firms tend to be in a perpetual state of reacting to new patterns of criminal behaviour and addressing enforcement actions instead of proactively disrupting criminal networks today and anticipating the challenges of the future.”

New kinds of financial crime, including synthetic identity fraud, are also exposing the weaknesses of contemporary financial crime prevention systems. 

Synthetic identity fraud involves the use of synthetic IDs – created with a combination of true and false information rather than a completely stolen identity – to apply for credit. The largest synthetic ID ring detected so far racked up $200 million from 7000 synthetic IDs and 25,000 credit cards. 

“This fraud typology is difficult to detect since the limited know-your-customer (KYC) data most firms have collected [is] insufficient to detect fake individuals early in the process,” Dr Harmon said. 

“The most effective approach to combating this is to leverage advanced machine learning (ML) techniques coupled with a more holistic (i.e. enterprise) view of KYC through integrating other data sources from internal and external sources.

Many financial institutions rely on “static detection rules” that aren’t up to dealing with the ever-changing nature of financial crime. Dr Harmon believes that institutions need to develop a “machine learning-driven environment” that has dynamic rules and embedded detection models.

But regulators and law enforcement are lagging too – research on the EU market estimates that only 1 per cent of criminal proceeds are confiscated by the authorities. 

“Financial crime has become increasingly pervasive and permeates all levels of the financial services industry,” Dr Harmon said. 

“Criminal networks are creative, connected, collaborative, and ready to exploit any opportunity inside or around the edges of business operations. We now even have state-sponsored actors involved.

“All of this is deeply concerning, not only to the financial services industry and our regulators but to society at large.”

 

Financial crime needs a new approach
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