Most transactions flagged as fraud are false positives, and they are driving unnecessary costs. In this podcast, David McLaughlin, CEO and co-founder of anti-fraud vendor QuantaVerse, discusses the conflicts chief risk and compliance officers face daily, how to automate fraud investigation, and whether automation helps or hinders the fight against fraud and money-laundering.
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“The industry standard is about a 95% false positive rate,” McLaughlin told Bank Automation News, saying that number comes out of a transaction monitoring system (TMS). “We have certainly seen 90% and above from our customers before we deploy our solution to help them lower false positives.”
QuantaVerse uses artificial intelligence (AI) and machine learning to automate financial crime identification and investigations. The solution works with rules-based TMS, identifying potential risks before a system processes transactions, and examining transactions that were not flagged, post TMS.
The company’s tech also automates the fraud investigations; in fact, about 70% of anti-money laundering (AML) investigations can be automated, McLaughlin said. Financial institutions have used the company’s solution to reduce a 20-minute alert triage down to five minutes, a company spokesperson told BAN. The solution automatically generates a report on flagged transactions. The company also last month added a new report to support the specific needs of Level 1 AML compliance teams. Level 1 is the initial process utilized for weeding out false positives.
Banks that are able to reduce the number of false positives in systems that automatically flag them can help risk officers focus on real crimes, McLaughlin said.
“We have focused pretty heavily on finding, deriving and improving, correcting that bad data so that those false positives will go down,” McLaughlin said. Fewer false positives lead to fewer alerts, allowing employees to focus on that the instances of risk that require human interaction, he said.
Bank Automation Ignite, on April 13-14, is the event for inspiring automation initiatives and investment in financial services. At the virtual event, financial services professionals can discover new use cases and technologies that are accelerating automation in banking. Learn more and register at www.BankAutomationIgnite.com.
The following is a transcript generated by AI technology that has been lightly edited but still contains errors.
Good day. I’m Loraine Lawson of Bank Automation News. Recently I spoke with David McLaughlin CEO and co-founder of QuantaVerse, which uses AI and machine learning to automate financial crime identification and investigations. We talked about the internal conflict compliance and risk officers face every day and the role of automation in reducing false positives in transaction monitoring systems.
Welcome, Mr. McLaughlin to the Buzz. Recently, you said there was a conflict inherent to the job of Chief Compliance or chief risk officer. When we had talked about what chief risk officers are worrying about at night? Can you explain what that conflict is?
Okay. Sure, Lorraine. You know, it’s a similar conflict that any manager has that runs in operation, you know, they are trying to do as good a job to make operations run smoothly and not have issues come up, whether it’s a trading or settlement or backroom operation, the difference with risk, and so you know, that that conflict is, how do they deliver what the organization needs to deliver from an operational standpoint, but their cost center? And so how do they deliver that without busting the bank and spending too much money on their on their operations? The difference with compliance and risk, and specifically in the AML Compliance area is that the downside of failure is much more significant. it there is personal risk that compliance officers carry with the regulatory regulators and law enforcement, compliance officers had been fined. They’ve been disbarred from the industry. They’ve had their reputations tarnished, so they they can’t get hired again. So they all know this, and they’ll carry this burden of accentuated burden of how do they deliver what the organization needs them to deliver and run a good strong AML financial crime compliance program? And how do they do that in a at a cost that is appropriate for the organization? But how do they do that without putting themselves personally in their organizations at big risk with regulators and law enforcement? So that’s that that’s the conflict that was referring to and it’s just much more accentuated with a compliance or Chief Compliance or chief risk officer.
And your solution Quantaverse, in part is designed to help help them do the job. And so can you give us an overview of what Quntaverse does and maybe what you help automate?
Yeah, sure. So that, you know, this, this conflict and this dual mandate that they have is something that we understood and heard from compliance folks very early in the development of our company. So, we intended out of the gate to help them with both of these not just a pure automation efforts are not just a pure risk reduction effort, but but a solution that helps them manage both both of these challenges. And so, what we’ve done is create a capability and a solution that enables them to lower the risk in a couple ways, and enables them to do so in a way that also lowers the cost to the organization, the overall cost of their compliance program. So, we have created the ability to lower risk by finding instances of money laundering that their current systems might be missing, but on we’re lowering risk. You know, even maybe even more importantly to the compliance officer, we’re lowering the operational risk of the organization through automation. So you know that it’s a very heavily human dependent environment today prequantum ers, and there’s a big role and important role for humans. But humans have been asked to do things in an AML financial crime compliance program that they’re not really great at. And that is about prot following the exact same process, data governance using the same data sourcing the same data, seeing the forest and the trees of that data, finding out what is important and what’s not important. And our automation efforts are really about controlling and managing that operational risk. You know, the last thing that a compliance officer wants to hear during a regulatory audit is the regulator to, to share with them two cases with the same fact pattern that their investigators made a different decision on, you know, that will that will make a compliance officer sweat if he has to sit in front of the regulator, and explain why his investigators came to a different conclusion on a very similar fact pattern. And so automation can can manage that kind of risk, that kind of operational risk by following the same best industry practices over and over and over again. So that’s the two ways that that we’re helping risk lowering the false negatives, and managing the operational risks through automation. And then on the cost side, there is a natural cost benefit by being able automate. And sometimes that cost benefit is seen through growth in the business growth in the transactions growth in the customers, without necessarily having a linear growth in the number of compliance staff that has has to manage that. So there are a couple ways that our our customers are receiving the benefits or accruing the benefits of that. At automation. Most of the time, it is through growth of revenue without growth of expense.
So false positives are major concern and industry and you specifically said you address that how do you address that what’s what’s going on there behind the scenes?
Yeah, another great efficiency play that we are helping our customers with, you know, false positives are a big driver of the costs unnecessary cost the the industry standard is about a 95% false positive rate that comes out of out of a TMS we have certainly seen 90% and above from our customers before we deploy our solution to help them lower false positives. The way that we are we are doing it is by improving the data. Prior to it going into a TMS there’s oftentimes wrong or missing data in a transaction file that if corrected, or appropriately found, or appropriately derived, prior to going into a TMS will have a dramatic impact on the false negatives that come out. And easy example, this is jurisdiction, cross border transactions with a Counterparty that’s not the customer, the bank. If the person that coded in that transaction at a wire room, didn’t know the jurisdiction of the Counterparty and left it blank, they are supposed to default that blank missing country code jurisdiction to the highest risk, which makes sense, you would, you would want to assume that a transaction is if you’re trying to find a instance of a financial crime is coming from a risky jurisdiction. So what we have found is that by accurately deriving that jurisdiction, we significant majority of the time, they are not coming from or going to a risky jurisdiction, just the person that entered it into the wire and the wire room didn’t know what what the country code was. So there is just Matt, significant amounts of data that when wrong or when missing, will drive false positives. And we have we have focused pretty heavily on finding deriving and improving correcting that that bad data so that those false positives will go down and less false positives means less alerts, of course, which means the human workforce can focus on that the instances of risk instances of potential money laundering that are significant and complex, and that are really need human interaction with you know, it’s not valuable to anybody to, to spend 30 minutes for a level one investigator level one analyst to spend 30 minutes to, to decide that the transaction was going to Paris, Texas, and not Paris, France, you know, that’s just not a not a good use of anybody’s time. And so that’s the kind of problem that we’re solving and the false positive reduction.
Okay, one thing we wonder, is we, of course, talk about automation here. But does does automation of transaction monitoring systems make your job harder or easier?
Well, so I view the transaction. I think that the the question, that question is one that I will answer from the perspective of our customer. And the reason I say that is, it’s irrelevant, whether it makes my job harder or easier, we’re here to serve our customers, and if an automation of their operations makes their life easier, you know, I want to do that. And so, we are trying to, and working to drive automation to the entire investigations and, and transaction monitoring process. And so, makes their, it gives them an ability to make their jobs, make them do be able to do their jobs better. So what I mean by that is, I don’t know if it makes it easier or harder by having automation in their shop. What it does is take the the, the insignificant work load, by and by insignificant I mean unimportant workload off of their desks and off of their employees desks, and enable them to focus on what is really important in a compliance organization. So, you know, we want to automate all those things that are that are somewhat irrelevant to managing financial crime risk. And if we can automate all those things that are irrelevant to managing financial crime risk, and we can enable our customers to spend their time and focus and energy on those things that are most important, I.e. complex cases that need human involvement, and highly, highly trained and highly skilled workforce to apply their judgment and their experience and their knowledge of their own institutions risk profile. If we can do that we have enabled them to do their jobs better. And that’s the end goal of this, you know, we serve, we’re lowering risk. We’re lowering cost managing costs, but really, we want to enable them to do their jobs better. And so I think it’s not a harder or easier, it’s a better.
Okay, we’ve been speaking with David McLaughlin of Quantaverse, thank you so much for your time.