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How Big Data Analytics Can Help Track Money Laundering to Stop Terrorist Activities

19/01/2015 by Sharon Shahzad

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Criminal and terrorist organisations are increasingly relying on international trade to hide the flow of illicit funds across borders. Big data analytics may be the key to tracking these financial flows.

For the past decade, governments around the world have established international anti-money laundering (AML) and counter-terrorist financing efforts in an effort to shut down the cross-border flow of funds to criminal and terrorist organizations. Their success has encouraged criminals to move their cash smuggling away from the financial system to the byzantine world of global trade. According to PwC US, big data analytics are becoming essential to tracking these activities.

"Today's trade-based money laundering activity goes beyond traditional laundering of criminal funds to include terrorist financing and intentional efforts to circumvent international sanctions," says Vikas Agarwal, a managing director in PwC's Advanced Risk & Compliance Analytics practice, which recently released the whitepaper, Goods gone bad: Addressing money-laundering risk in the trade finance system. "To evade detection, traffickers are becoming more sophisticated in their methods, and financial institutions should remain two steps ahead by deploying advanced analytical and statistical techniques. It's an issue that has become a top concern in board rooms and C-suites across the globe."

It's easy to understand why criminal and terrorist organizations would turn to the global merchandise export trade to hide the movement of their funds. It's a classic needle in a haystack — an $18.3 trillion business formed of a "web of complexity that involves finance, shipping and insurance interests operating across multiple legal systems, multiple customs procedures, and multiple languages, using a set of traditional practices and procedures that in some instances have changed little for centuries," PwC says.

Watching the Money Flow

There's no real way to quantify how much money criminals are invisibly exchanging using this system. PwC notes that the Global Financial Integrity (GFI) research and advocacy organization estimates that 80 percent of illicit financial flows from developing countries are accomplished through trade-based money laundering (TBML), from more than $200 billion in 2002 to more than $600 billion in 2011. GFI believes more than $101 billion was illicitly smuggled into China in 2012 via over-invoicing, which is only one of the common TBML techniques.

"At its core, trade finance is an old-fashioned business," the report says. "As other industries have adopted more technology- and data-driven infrastructures, trade finance has remained extremely document-intensive and paper-based, moored on a framework of instruments, systems, and practices that have proven their effectiveness and earned global trust over the generations."

This article has been extracted from http://www.cio.com, please click on this link to read the article in full http://www.cio.com/article/2871684/big-data/how-big-data-analytics-can-help-track-money-laundering.html

Montash is a multi-award winning global technology recruitment business. Specialising in permanent and contract positions across mid-senior appointments across a wide range of industry sectors and IT functions, including:

ERP Recruitment, BI & Data Recruitment, Information Security Recruitment, IT Architecture & Strategy Recruitment , Energy Technology Recruitment, Demand IT and Business Engagement Recruitment, Digital and E-commerce Recruitment, Leadership Talent, Infrastructure and Service Delivery Recruitment, Project and Programme Delivery Recruitment.

Montash is headquartered in Old Street, London, in the heart of the technology hub. Montash has completed assignments in over 30 countries and has appointed technical professionals from board level to senior and mid management in permanent and contract roles.

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