Welcome to the ACFCS Financial Crimecast, where we highlight key trends and talk to top thought leaders in the industries involving financial crime and compliance.
In our latest podcast, we are talking with David McLaughlin, the CEO and founder of QuantaVerse, which uses data science and artificial intelligence (AI) to help institutions better identify financial crimes.
But first, a bit about McLaughlin: He spent six years as a naval officer and also graduated from the highly regarded TOPGUN program, eventually completing a combat tour in the Persian Gulf. Prior to starting QuantaVerse, he held top positions with leading technology, security and financial services firms.
Currently, how banks manage anti-money laundering (AML) compliance programs domestically and internationally is a hot button issue with federal regulators, investigators, global watchdog groups and even the banks themselves as institutions spend tens of billions of dollars annually to identify and report on suspicious activity – with a bulk of resources spent on dispositioning an avalanche of false positives.
That is why terms like AI, machine learning and regtech are current industry buzzwords, with many banks tinkering with improving the ratios of transactional monitoring alerts to suspicious activity reports (SARs), the finial of a strong compliance program adequately analyzing transactions and sending detailed, timely and relevant intelligence to law enforcement.
McLaughlin shared his insight on a bevy of topics in the AI space, including:
How can AI help bank AML teams either increase efficiency or improve results?
There has been a lot of discussion about how AI can help AML, but how can it help banks and corporates on the corruption side and, beyond that, on efforts to converge financial crime departments?
What are some concrete examples you have seen where a bank had one ratio of alerts to false positives to SARs and those figures improved, either lowering alerts, getting better alerts to staff or creating SARs in new areas, and lowering less relevant SARs in other areas?
What do you think the future holds for AI and financial crime compliance, investigations and analysis?
Lastly, there has been a great debate in the AI and AML world and I would like to see which side of the fence you fall. Some have said that as AI matures in bank AML programs, banks will be able to trim the ranks of rank and file compliance teams, meaning fewer compliance analysts who can do more.
Others have said, no, AI-enhanced systems will find more potential instances of financial crime, necessitating larger compliance teams as banks will be getting richer, more relevant intelligence that would need to be investigated. What do you think will happen?
You can listen to his answers with the below player:
About the speaker:
David McLaughlin is CEO and founder of QuantaVerse, which uses data science and artificial intelligence to help institutions better identify financial crimes. He spent six years as a naval officer, starting in 1986 as an Ensign in the U.S. Navy and attending flight school in Pensacola, FL.
McLaughlin is a graduate from the highly regarded TOPGUN program, and completed a combat tour in the Persian Gulf where he was awarded the Distinguished Flying Cross and two Air Medals for bravery in combat.
Prior to founding QuantaVerse, David held senior executive positions with IPR International, NES Financial and SEI.
Excellent point, David. Thank you for taking time to listen to the podcast and post some thoughtful comments. That might be a great question for a follow up conversation with David, the CEO of Quantaverse. I would suggest also reaching out to the company directly as they are very responsive related to questions about their technology and what is happening with AI and AML in the sector overall. Feel free to send an email to Mark Tordik, their PR contact at, firstname.lastname@example.org. Have a great day and feel to reach out to me directly if you have any more questions about ACFCS Content.
VP of Content
A comment David made which I think needs more discussion is how his company and frankly all vendors in this space can use their platforms across all their clients(financial firms) to generate 'collaboration' using back-side aggregation services or in his words 'what works well for one helps everyone'. this would help compliance people improve the machine learning and would help the compliance people as the machine's are learning both from the financial firm but from the vendor experience across all clients.