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Google Cloud Attacks Money Laundering with AI | July 2023

As we’ve previously discussed, artificial intelligence (AI) is transforming the money business from wealth management to counterfeit detection. Now, Google Cloud has introduced anti-money laundering AI to detect potential money laundering activity. 

What is Money Laundering? 

Laundering money refers to making money from illegal and illicit activities appear as if it is from a legitimate source. These activities include drug trafficking, bribery and corruption, gambling, embezzling, terrorist funding, and more. “Laundering” is a play on words to suggest “dirty” money is cleaned. 

Money is laundered through a complex series of transactions before it is withdrawn from a legitimate account. Detecting laundered money can be difficult, even more so now that electronic money is so common. Online banking, online payment services, peer-to-peer payment apps, cryptocurrencies, and more have added to the complexity. 

Detecting Money Laundering Activity 

Until now, financial institutions have relied on humans to refine their anti-money laundering systems. Google Cloud’s tool puts AI at the helm. Other machine learning tools already exist in this area that combines human judgment with machine learning capabilities, but Google’s technology (called Anti Money Laundering AI or AMLAI) does not use the same rules-based programming. Early adopters of Google’s tech include HSBC (England), Banco Bradesco (Brazil), and Lunar (Denmark). 

With existing technology, people calibrate anti-money-laundering tools and input their own rules manually. With Google’s tool, users cannot input rules, but they can guide it with their own risk indicators.  

Google’s justification for this approach is that current systems with manually inputted rules generate too many false positives, which can overwhelm compliance employees who review each alert. In the case of HSBC, a London-based financial services company, AMLAI cut the organization’s alerts by 60 percent and improve the accuracy of the alerts by up to four times. 

AI Could Be a Tough Sell  

Though Google’s AMLAI could potentially improve money laundering detection, there is some resistance to machine learning models. For example, there could be regulatory hurdles. Additionally, sometimes human intelligence is superior to machine learning. It can be much easier for people to understand contextual information that may not be addressed by AI tools.  

Google hopes to put these concerns to rest by delivering results that are easily explainable to analysts, risk managers, and auditors. AMLAI won’t just flag one suspicious transaction, it will compute a consolidated risk score. It analyzes trends and behaviors to provide any contextual factors and underlying transactions that gave the customer a high-risk score. Google says its tool doesn’t just provide answers, it shows its work. 

In the Classroom 

This article can be used to discuss money (Chapter 15: Money and the Financial System). 

Discussion Questions 

  1. What is money laundering? 
  2. How is Google’s AMLAI different from other tools?  
  3. Why is there resistance to machine learning models? How does AMLAI address these concerns? 

This article was developed with the support of Kelsey Reddick for and under the direction of O.C. Ferrell, Linda Ferrell, and Geoff Hirt. 


Dylan Tokar, "Google Cloud Launches Anti-Money-Laundering Tool for Banks, Betting on the Power of AI," The Wall Street Journal, June 21, 2023,  

Ryan Morrison, "Google Cloud Launches AI-Powered Anti-Money-Laundering Tool," Tech Monitor, June 21, 2023,  

Tristan Greene, "Google Launches 'Anti Money Laundering AI' after Successful HSBC Trial," Cointelegraph, June 22, 2023,

About the Author

Geoffrey A. Hirt of DePaul University previously taught at Texas Christian University and Illinois State University, where he was chairman of the Department of Finance and Law. At DePaul, he was chairman of the Finance Department from 1987 to 1997 and held the title of Mesirow Financial Fellow. He developed the MBA program in Hong Kong and served as director of international initiatives for the College of Business, supervising overseas programs in Hong Kong, Prague, and Bahrain, and was awarded the Spirit of St. Vincent DePaul award for his contributions to the university. Dr. Hirt directed the Chartered Financial Analysts (CFA) study program for the Investment Analysts Society of Chicago from 1987 to 2003. He has been a visiting professor at the University of Urbino in Italy, where he still maintains a relationship with the economics department. He received his Ph.D. in finance from the University of Illinois at Champaign-Urbana, his MBA at Miami University of Ohio, and his BA from Ohio Wesleyan University.

Profile Photo of Geoffrey A. Hirt