Advanced analytics: An advantage in fighting international money laundering

By Daniel Teachey, SAS Insights Editor

Trade-based money laundering (TBML) funds the world’s largest illicit markets – counterfeit goods, narcotics, people – and finances global terrorism. But you rarely hear about it in the media. Yet, TBML has its roots in early civilization.

Alternative remittance systems, also known as informal value transfer systems, have thrived all over the world ever since the establishment of trade. With strong and deep cultural roots, they represent ancient methods of commerce. Often anchored in the loyalty and discretion of indigenous, ethnic and family networks, today these highly evolved human-centered systems remain safe, fast, reliable and culturally acceptable.

But, as global finance has evolved, these systems have become incompatible with modern expectations around transparency and can seem alien to many Westerners.

The good news: even illicit trade leaves a big data trail. The bad news: the big data trail is riddled with intentionally manipulated information. But this is exactly where advanced analytics comes in.

Much like Pakistan’s better-known “Hawala” (with which Western governments became familiar after 9/11 for its ties to terrorism finance), China’s own underground banking system (“Fei ch’ien”) has been quietly operating and thriving for centuries. In fact, former Canadian ambassador to China David Mulroney once called China the “#1 exporter of hot money in the world.”

He could be right, as the world’s second largest economy now loses far more in illicit capital outflows than any other emerging market. But not only is China’s alternative remittance system operating against the best interests of its formal economy, it is also creating and reinforcing opportunities for organized criminal groups to move large amounts capital around the world.

Recently, SAS sponsored “Lifting the Lid on Chinese Underground Finance,” a breakfast seminar co-led John Cassara, former Treasure Special Agent and author of Trade-Based Money Laundering: The Next Frontier in International Money Laundering Enforcement.

Cassara explained how TBML has become a highly effective method of disguising and transferring value of illicit origins through the falsification of trade transactions. Due to the sheer volume of international trade flow, large-scale TBML goes by virtually undetected. It is increasing in frequency and gaining a reputation for funding some of the world’s most nefarious activities. The regulatory holes and cultural supports that breathe life into TBML are an indication of why it has never been cracked by Western governments – despite the fact that it cheats them of billions of dollars, annually.

Luckily, big data and advanced analytics are making it easier to detect and trace illicit financial transactions, empowering governments to confront and minimize threats, and hold onto their money.

To better understand how advanced analytics paired with big data can detect TBML, consider the way these illicit systems use deliberate, but false, invoicing. To move money out, you import goods at overvalued prices or export goods at undervalued prices; to move money in, you import goods at undervalued prices or export goods at overvalued prices.

In the seminar, Cassara mapped out the growth of TBML and its connection to China’s informal value transfer systems. He was followed by Global Financial Integrity (GFI) economists Joseph Spanjers and Matthew Salomon, who detailed evidence of massive illicit trade outflows from China via trade invoicing.

The good news: even illicit trade leaves a big data trail. The bad news: the big data trail is riddled with intentionally manipulated information. But this is exactly where advanced analytics comes in.

Advanced analytics can help sift through (and find patterns within) mounds of records, such as global trade logs, wire transfers and social media posts. It can rapidly separate factual from fictional data and isolate evidence of illicit behavior and follow it to its source. Anti-money laundering analytics uses a data-driven approach to whittle down, categorize and prioritize certain data, effectively streamlining and improving investigative efforts.

By more heavily weighing a specific set of attributes in a given data set – such as a shipment’s path and frequency – analytics spotlights the most significant information about a transaction, including:

  • Origin and amount
  • Where it’s going or where it went
  • Related dates
  • Notes on any red flags it may have raised
  • The specific names of participating companies and people.

Using new and historical data, the analytics can provide country-based alerts that equip analysts with the real-time tools to anticipate threats.

Global crime groups may have more networks and resources than ever before, but advanced analytics solutions are more nimble, efficient and insightful than even the most polished human systems. It will take the most modern of technologies to combat crimes rooted in the traditions of the oldest civilizations.


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