As terrorist attacks make headlines around the world, banks and other financial institutions have started using artificial intelligence to bring about ending terrorism.
Banks are now integrating machine learning into their systems to mine large quantities of data that will help trace account anomalies and suspicious transactions. Ending terrorism will surely require the policing of common mediums of extremist and criminal activity.
For years now, anti-money laundering systems have been put in place to help banks flag unusual financial activities. In the aftermath of the September 11 U.S. terror attack, banks turned to these legacy tools to catch terror-related transactions.
While anti-money laundering systems have been essential in regulating bank transactions, they are not enough to trace activities related to terrorism and organized crimes.
The systems can flag transfer of large funds from one country to another. However, terror groups like ISIS have grown wiser and resorted to smaller, targeted attacks that only require little funding. This move made it impossible for systems relying on hard-coded “if-then” rules to catch them.
Terrorist groups are highly dependent on the financial assistance sent by their supporters from different parts of the world. More often, this money came from ransoms and other crime related activities like drug trafficking.
Curtailing this relationship is one facet of successfully ending terrorism.#QuantaVerse developed an #AI tech to help banks stop money-laundering.Click To Tweet
Small transaction patterns made by criminals in hiding will not raise red flags from the anti-money laundering systems. Not unless these systems are integrated with artificial intelligence.
Dan Stitt, director of financial crime analysis for the Wayne, Pennsylvania-based firm QuantaVerse, said:
“It’s a surgical approach to finding a needle in a haystack.”
QuantaVerse is the company behind some of the world’s biggest banks’ AI technology. Currently, their technology has already helped the DEA identify a Panamanian man involved in a big money-laundering scheme.
Development of AI for the banking industry is still in its early stage. However, financial regulatory bodies already showed support and expressed high hopes for the potential of the tool. Kevin Petrasic of White & Case law firm stated:
“Machines are able to take in multiple additional data points and analyze those data points in a way that may not seem obvious to human beings.”
Right now, banks are still spending billions of dollars on anti-money laundering systems afflicted by false positive reports. A Dow Jones survey of more than 800 anti-money laundering experts showed that almost half of them are disappointed with the accuracy of the system because of the false positive alerts.
David McLaughlin, the founder of QuantaVerse, said:
“That’s billions invested—a lot of humans investigating the flags a legacy system will generate, and a large majority of those turn out not to be financial crimes. Meanwhile, the real financial crimes are going unnoticed.”
How QuantaVerse’s AI Technology Works
QuantaVerse’s team of data scientists developed an AI technology that learns predictors on its own. Its algorithm was trained by experts on several years’ worth of data from one of the top five biggest banks in the world.
As per Stitt, the system was trained to analyze and determine what a good or bad behavior looks like without any human intervention. Some factors that affect the judgment of the AI system include how quickly the money is being moved, where it is moving, and the amount that is being transferred.
Aside from that, the system also looks at anomalies in invoicing number sequences.
Apparently, organized crime groups involved in money-laundering activities tend to falsify invoices to make crime transactions look legitimate. QuantaVerse’s AI technology can flag these transactions by spotting duplicate invoices and system errors.
QuantaVerse’s AI system can also detect potential money-laundering transactions by looking at account history and its existing relationship with other bank accounts. Traditional systems can only check up to three months’ worth of data while QuantaVerse’s system can handle up to three years of bank history.
The effectiveness of QuantaVerse’s AI technology was put to the test when it identified a series of invoices for significant amounts of money transferred between businesses that have the same owner. The company reported the incident to its client, and after a year, DEA announced the arrest of Nidal Waked on charges of money laundering.
As syndicates and extremist groups are moving desperately to carry out heinous crimes, a fully developed AI technology can be the key that will help stop the reign of terror that plagues our world today.