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3 min read

How Artificial Intelligence Can Help Financial Institutions Put an End to Cartel’s Illegal Border Business Bonanza

Current estimates suggest that Latin American cartels who facilitate illegal U.S. border crossings net $400 million each month. These, and related windfalls, must be laundered through the financial system to facilitate other cartel business and fund the lavish lifestyles of the cartel kingpins and their senior management.

Laundering these flows should create opportunities to uncover criminal operations, but for financial institutions using antiquated technology and error-prone processes, this is an embarrassingly huge problem. Even though they are required to identify and report suspected money laundering, banks and other financial institutions are currently failing to find an estimated $2 trillion in dirty money transacted through their operations each year. This puts them at risk of steep penalties and reputational damage that could be difficult, perhaps impossible, to recover from.

To better understand how financial institutions can navigate these risks, let us examine:

  1. The root of the problem
  2. The U.S. government actions
  3. What institutions can realistically do to help keep cartels in check

Following the Money

According to sources, the average Latin American border-crosser pays $4,000 to be smuggled into the U.S. Anyone likely to attract more scrutiny on U.S. soil is charged significantly more. A group of Chinese nationalists recently caught at the US Southern Border confessed to paying $50,000 each for cartel services.

The revenue generated by facilitating border crossings fuels the growth of the cartels’ other business units, including illicit drug sales and human trafficking. These, in turn, generate statistics that no-one likes to see. The CDC recently recorded the highest number of overdose deaths in a 12-month period – more than 81,000 between May 2019 and May 2020. The numbers from the International Labor Organization are just as harrowing. A 2017 report noted that 25 million humans are victims of forced labor (4.8 million of those were trafficked for forced sexual exploitation).

Human trafficking is a multi-billion-dollar problem hidden in plain sight.  Despite the fact that billions of innocent lives fall victim to this heinous and highly sophisticated criminal activity, fewer than 4,000 human trafficking convictions were reported worldwide in 2018. These numbers reflect an alarming disconnect between these criminal activities and law enforcement’s attempts to uncover them.

Understanding the Law

In the meantime, institutions are expected to comply with the Anti-Money Laundering Act (AMLA) enacted by Congress at the start of 2021. The U.S. government is using the legislation to promote technological innovation for AML and Combating the Financing of Terrorism (CFT). Innovation and information-sharing are being encouraged and institutions are being assessed on how they incorporate national AML/CFT priorities into their compliance programs.

Civil penalties for a first Bank Secrecy Act (BSA) violation can be twice the maximum, or three times the violator’s profit resulting from the violation. Individuals convicted of BSA violations must now repay profits and bonuses. In short, the penalties for non-compliance are far greater than the cost of compliance.

Find the Money — Destroy the Syndicate

The goal of the AMLA is not to incumber institutions, but rather to rally their help in fighting the financing of illicit drug operations, human trafficking, corruption, and terrorism. It is to encourage institutions to embrace technology capable of identifying, tracking, and reporting the $2 trillion in laundered money that goes unchecked each year.

New technologies such as AI and machine learning can systematically scan large amounts of data to identify patterns, typologies, and anomalies indicative of cross-border trafficking that investigative teams may not have the capacity to spot. These red flags include:

  • Victims who share identical bank account information (including but not limited to phone numbers and home addresses)
  • Account activity is inconsistent when compared to account holders’ employment information
  • Techniques designed to shuffle transactions and disguise the origin of money including funneling, structuring, bridging, and parking.

The innovative application of technology is transforming a social issue and redefining how public and private sectors can work together to tackle the world’s biggest problems.

“We can be proactive. We can now examine transactions using cognitive computing technologies,” explains David McLaughlin, Founder and CEO of QuantaVerse. “We can now see the syndicate and identify the players in that syndicate. We do not have to wait for a victim to be able to identify a crime.”

QuantaVerse, the leader of AI and machine learning software purpose-built for identifying money laundering inside banks and payment services businesses, has developed the technology to identify financial crimes and proactively bring illegal cartels to justice. The QuantaVerse Financial Crime Investigation Platform makes it harder for criminals to move dirty money around by gathering data, identifying transaction patterns and discovering anomalies that indicate when money is being laundered.

To learn more about how financial institutions are using AI software to separate cartel kingpins from their ill-gotten gains and hamper their operations, please visit: