Evelyn has two skills. The first one is name sanction screening alert review, where you’re comparing your existing counterparties and you’re screening them against watch lists. So all of those sanctions lists, OFAC lists, the UK list are one of those, you’re screening your counterparties against that to ensure that none of your existing customers are sanctioned individuals or sanctions, because there’s a huge risk with that.
Evelyn’s other skill is adverse media monitoring. And that is what you’re speaking about there, which are adverse media review. So what does Evelyn do here in her adverse media monitoring skill? She searches and reviews all the media sources there are to determine if any mentions of your counterparties are relevant and/or adverse. She can consume that information. She’ll rank it, prioritize it, and then either send it for a review by your team, or she can actually disposition it and say, “You know what, this mention here, there’s no risk to it. You don’t need to look at it.” She’ll conduct the search, gather the data, record the evidence, and then present it to your teams.
Let’s have a look. To understand the real benefit of Evelyn, we kind of need to understand the existing landscape. I was one of these screening adverse media analysts back in the day. If you want to screen your counterparties, you have to go out to a new source. We’re using Google News here, but you could just as easily use any of the ones that Evelyn integrates with: Dow Jones Factiva, LexisNexis, RDC or any of those. But right now you’d have to go and you’d have to screen your counterparty. We’re looking for Alexander Morris. You type it into your search and all of these results come back, and you don’t know which one to look at. There are hundreds of them. They’re not ranked, they’re not prioritized. You don’t know where to click. You don’t know what to look at, but you’ll have to still go through each of them to understand the content, to understand the context, to understand if there’s any risk involved. But then you’ll get a bit better at your job and you’ll narrow the search. You’ll add some keywords, you’ll add “fraud,” or you’ll add “money laundering,” or you’ll add “trafficking” or something like that. And that will reduce the amount of results you get. But you still have the same issue. You still need to go through each of them, each of these news articles, understand the context, understand the risk, and the hardest part — you need to make a decision then at the end of this.
What Evelyn does is that she does all of this for you. She can, again, she’ll go out, she’ll search all of these media sources. And she can search multiple media sources. She can do Google, LexisNexis, RDC, Dow Jones Factiva, to determine relevance. And if any mentions of your counterparties are adverse, she’ll bring it all into one really easy to use WorkFusion UI.
Let’s check what that looks like. Evelyn went out she searched Alexander Morris, and you can see here what that does. Clicking the case, it brings the user into a summary review where they can then review the articles that Evelyn has dispositioned, as well as her comments. All of the dispositioned articles down here, there’s 18 of them. She’s already done the work for you and determined that they’re false positives, so low risk, false positive, and she’s already auto-generated those comments. So, “Not a match. Subject’s age does not match with age in the finding,” “Not a match. Subject was identified in the finding, but is not responsible for the alert.” But the important thing is she’s actually gone through all of these and highlighted the high-risk articles for your team.
Let’s look at what they look like. We clicked here in the “Owner ‘violated’ by salon break-in.” Alexander Morris is mentioned here. When you select an article, you come into the detail screen, you’ll see the full text of the article, the risk score of 0.71, and other important information for the user to understand. All of the keywords, all of the high-risk countries. It highlights the counterparty that’s been screened. We can see here, Alexander Morris really clearly. It’s very easy for the user to come in and understand how Evelyn came to what she decided. She decided here it needs investigation. What does that mean? It’s pulling in your agent to help Evelyn understand the decision she made.
I’m going to update the status here. I’ve reviewed this. I think it’s a false positive. You can change it to false positive. And then that decision, when I change it, gets fed back into Evelyn. I’m going to update the case with comments. I’m saying this article is a false positive. Screened customer location does not match location in article Truro. I’m going to close this investigation and move back to the screen. And again, as I said earlier, Evelyn, she’s really curious, and she’s learning all the time. Me, or your user, or your agent, or a member of your team updating Evelyn’s decision matrix like this, it feeds back into her so that the next time she encounters this scenario, she’s going to be better equipped.
Let’s look at the next one that we need to review: “Bedbugs lead to arrest.” Over here on the left hand side, just a quick one, where there are blue markers, it lets you know what articles you have yet to read. We’ve read “Owner ‘violated’ by a salon,” and now we’re looking to “Bedbugs lead to arrest,” right? And Evelyn has actually suggested this as a true positive. According to court documents, Alexander Morris, aka Alexander Luna, and we’ve concluded this is a true positive. So again, we can close investigation and we can move on. Or if we want to review any further, we can add extra comments here too.
When an article is reviewed and a comment is added, it moves from the “articles to review” section to the “dispositioned” section and your reviewer’s name. This will be the name one of the agents in your team. It’s highlighted on the screen and their decision comment is added. There’s full transparency with what’s happened with the case. And if this needs to be pushed to a higher level analyst, or it needs to be pushed to level two or level three, they can come in and review the case too. And before closing the case, they can add comments or they can reassign, or they can leave specific articles tagged as “needs investigation.” So we want to close this here. And when the analyst is ready to close the case, you can add a case comment and you can choose the overall status for the case. This is a decision you make based off all the work that Evelyn has done for you. You can say False Positive, Needs Investigation or True Positive, but we’ve seen one of these as a true positive, so we’re going to mark this as True Positive and… Oh, one thing that’s important is that Evelyn flags articles that you’ll need to review. And then there are articles that she’s determined you don’t need to review because they’re low risk and she’s determined they’re false positive. The real benefit of Evelyn is that your team doesn’t even have to look at those, but we are really conscious about risk with WorkFusion; Evelyn is risk averse. She’s really concentrated on maintaining that a bank’s risk is pretty much zero or it’s close to zero as it can be using Evelyn. And when we want to close a case or when your agent wants to close a case, Evelyn will warn them that they are going to close the case without reviewing all of the articles. So it’s just a check to say, okay, you’ve read articles A, B, and C, but there might be 17 that you haven’t read. And those 17 are false positives. It’s just to check that to make sure they you’re comfortable moving on without doing that.
What’s the real benefit of Evelyn here is that she’s gone out and she’s done all the leg work for your team, and she’s done a lot of the decisioning and a lot of understanding what the risk is. And then you can be comfortable with all of the false positives that she’s determined. And we can save the case, having just analyzed, instead of looking at 25 articles, your agent can come in and just review two high-risk articles, make a decision and be comfortable and move on, and we can save and close it as a false positive or close it as a true positive.
And that’s Evelyn. So they’re her two skills. And they are two things that she’s really quite fantastic at.