Is AI Changing the Face of Financial Crimes & Money Laundering?
Moore’s Law used to guide the technology industry and its evolution, but a number of pundits called Moore’s Law dead years ago, mostly because innovation was moving too fast with the explosion of mobile, IoT (Internet of Things) and artificial intelligence (AI). What was Moore’s Law, you ask? By strict definition it was the description of the tech industry being able to, “double chip densities every two years” through innovation, but it was about more than just storage. It applied to all tech innovation. Today, Moore’s Law applies only to the slowest of techies — criminals who are just now using AI to steal money. They might evolve a bit slower than Apple’s engineers?
Regardless of their pedigree, FinCriminals are evolving and of late have fallen in love with artificial intelligence and its ability to produce bots, deep fakes and synthetic identities. Why? Because these tools make stealing money more efficient, safer and can run remotely, and as the tools themselves evolve they become easier to program. AI is such a broad term though. I digress. In terms of FinCrime, here are a couple of examples of how artificial intelligence is being used to steal money and identities:
Bots — An identity thief’s best friend is a bot that can scan thousands and thousands of stolen account records, searching for loopholes. Oftentimes, out of a stack of 300,000 records they might generate three leads? This is needle in a haystack stuff that only bots can accomplish.
Deep Fakes & Synthetic Identities — This is an area where I think AI gets a little freaky. In a case from 2019, the CEO of an energy company based in the UK was defrauded of nearly $250 million after some crooks used AI -based software to successfully mimic the voice of the executive’s boss, who was the chairman of a parent company based in Germany. Using AI to mimic this voice the thieves called the CEO, posing as the chairman, and had him wire funds to a Hungarian supplier. It worked, but then the thieves got greedy.
According to an article in the Wall Street Journal, instead of that one call the crooks made three calls. The second call was placed to confirm that the money transferred would be reimbursed to the CEO by its parent company, which was good, and then the third call asked for a second payment. Since that third call was placed before the original funds had transferred it raised red flags so he did not make the second payment. That being said, the original payment was moved to Mexico and distributed. There are no suspects.
And how is digital technology being used to launder that stolen money? Notice, I didn’t say AI or bots were laundering stolen money? In spite of headlines claiming a link between AI and money laundering, thus far that well is empty and there are no reported money laundering bots and/or AI programs on the cash washing scene, as of this writing.
That being said, the internet still exists, along with the darknet. Here are just two examples of how simple, online platforms are being used to launder money:
Online investment platforms — In last week’s post I discussed how money launderers are using digital platforms like Robinhood to launder stolen money. Though the platforms have stepped up security of late, this crime will continue until every loophole is shut down.
Cryptocurrency — There are a number of different schemes and services available on the darknet/darkweb that take advantage of weak government regulations and bad oversight by the cryptocurrency companies, such as Bitcoin, Dogecoin, Ethereum and more. Perhaps the best example is the case of Larry Dean Harmon, of Ohio.
According to the US Department of Justice, from 2014–2017 Harmon operated a company called Helix, a Bitcoin money laundering operation better known as a ‘tumbler’ or ‘coin mixer’ that advertised its services on Harmon’s darknet-based search engine, known as Grams. Harmon then created a network of partners who used Helix to send bitcoin to each other incognito, paying Harmon a fee. Over three years, Helix laundered over 350,000 bitcoin, which at the time was valued over $300 million dollars, for its mostly darknet customers.
Harmon’s crimes might seem fairly harmless from the outside looking in, but reality paints a different picture. According to Steven M. D’Antuono, Assistant Director in Charge of the FBI’s Washington Field Office, “Harmon admitted that he conspired with Darknet vendors to launder bitcoin generated through drug trafficking and other illegal activities.”
FinCriminals like Harmon are heroes on the darknet, but to those having their identities and bank accounts emptied, they are a menace. To the banks and the fiduciary companies that have to reimburse their customers, they are an expensive menace.
From the perspective presented above, AI seems like a win/win/win for the criminals, but realistically they have a ways to go. The problem for the gangsters to overcome at this point is not in how to engage AI in the stealing of people’s money, but rather how to use AI or bots to clean that money, without getting caught, in order to spend it. Yes there are darknet platforms that pop up from time to time, but is AI actually being used right now in the actual laundering process? As I stated above, nothing that I know of yet exists. I suspect in about three years we will see AI’s emergence on that side of the equation, per Moore’s (cybercrime) Law.
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