AI is a broad term covering multiple fields. For AML professionals, perhaps the most relevant subfield of AI is machine learning, which refers to the use of algorithms to continually improve a task, without the need for human intervention. Machine learning algorithms search for patterns within a given data set. Repeated recognition of patterns allows an algorithm to make ever more swift and accurate predictions. According to a survey of 296 UK-based AML professionals conducted by The Economist Intelligence Unit, the areas where respondents believe AI and advanced analytics can best be applied to combat money laundering are suspicious activity reporting (45%) and transaction monitoring (43%).

Dr. Akli Adjaoute, CEO of Brighterion, wrote this AI-focused piece as part of our 2018 year-end eBook. On Dec. 3, 2018, the U.S. Treasury's FinCEN and Federal Banking agencies issued a joint statement encouraging innovative industry approaches to combating money laundering, terrorist financing and other illicit financial threats. As a result, anti-money laundering (AML) has been occupying the headlines as of late. The financial industry has paid $321 billion in fines just through the end of last year, as estimated by Boston Consulting Group. JPMorgan had to pay more than $2 billion in fines due to violation of the Bank Secrecy Act, tied in part to the infamous Bernie Madoff scheme.

As a result, both the industry approach and regulatory framework are failing in the fight against money laundering. Despite the vast resources deployed by financial institutions to combat money laundering, the current approach is not delivering sustainable results. Money-laundering activity is estimated to be between 2 and 5 percent of global gross domestic product (GDP). In the United Kingdom alone, the social and economic cost is estimated to be least £24 billion a year. According to a report by Europol, around 10 percent of the Suspicious Activity Reports (SARs) filed by financial-services institutions lead to further investigation by competent authorities.

Singapore-based AI startup Silent Eight has won the top spot at the RegTech Association Australia's inaugural pitch fest this year. Silent Eight's artificial intelligence-based tools help financial institutions combat money laundering and terrorism financing. According to Silent Eight's website, it has a passion for AI and a relentless drive to revolutionise the science of due diligence. "To that end, we have invented a groundbreaking system with Artificial Intelligence at its heart, powering through with Machine Learning. Our system has proven so effective, we are working with a number of larger banks and financial institutions to give them a powerful tool to combat Money Laundering and Terrorism Financing."

By Anna Irrera NEW YORK – HSBC Holdings Plc has partnered with Silicon Valley-based artificial intelligence startup Ayasdi Inc to automate some of its compliance processes in a bid to become more efficient. The banking group is implementing the company's AI technology to automate anti money-laundering investigations that have traditionally been conducted by thousands of humans, the bank's Chief Operating Officer Andy Maguire said in an interview last week. The vast majority of anti money-laundering investigations at banks do not find suspicious activity, resulting in a waste of resources, according to the startup. In a pilot of Ayasdi's technology, HSBC saw the number of investigations drop by 20 percent without reducing the number of cases referred for more scrutiny, according to the startup. "It's a win-win," Maguire said.

NEW YORKHSBC Holdings Plc has partnered with Silicon Valley-based artificial intelligence startup Ayasdi Inc to automate some of its compliance processes in a bid to become more efficient. The banking group is implementing the company's AI technology to automate anti money-laundering investigations that have traditionally been conducted by thousands of humans, the bank's Chief Operating Officer Andy Maguire said in an interview last week. The vast majority of anti money-laundering investigations at banks do not find suspicious activity, resulting in a waste of resources, according to the startup. In a pilot of Ayasdi's technology, HSBC saw the number of investigations drop by 20 percent without reducing the number of cases referred for more scrutiny, according to the startup. "It's a win-win," Maguire said.