The call for a new approach of Transaction Monitoring is fierce. But actually, the new approach is already there.

Everyone agrees: the current way of Transaction Monitoring is no longer tenable. For many reasons (read ‘the five main pain points’). And some articles outline a future solution, for example for the opening of the blind spots and on the other hand counteracting the ‘false positives that come over and over again’. As an interesting article of Deloitte Luxembourg states: “Even if we are not there yet (…) the aim is to bring a more data-driven approach together with artificial intelligence and machine learning to deliver actionable insights and to create much less noise than the usual approach.” The good thing: we don’t have to wait for the new solution, it’s already there: CW360.

Love it, hate it, or just don’t understand it, Machine Learning and AI technology is here to stay. And in the world of compliance tooling, this is very good news.  With growing regulations and more responsibility of financial institutions to do their part, the move from a rule-based approach to monitoring with machine learning is not only desirable, it’s going to be inescapable. That’s why we built CW360, our premium SAAS solution, including Transaction Monitoring and Know Your Clients (KYC), for banks and Financial Institutions.

Rule-based vs Machine Learning

With business rules as the basis for transaction monitoring, algorithms compare transactions with scenarioswhich first have to be agreed upon before being manually added. A lot of time, a lot of effort for which the reward is often a lot of false positives (annoying, time-consuming to correct) or huge blind spots in fraud detection (high risk, unacceptable). On top of that, rule-based systems often use legacy software that simply can’t process the vast and real-time data streams critical for the digital space.

Enter the world of CW360, of AI and Machine Learning. Offering the chance to get insights into financial behaviors in ways that probably can’t even be imagined, machine learning allows us to move from a two-dimensional view of say, volume and frequency of transactions, to a multidimensional view on behaviors that would be impossible to detect using manual inspection.

User -confirmed false positives are ‘learned’ and won’t be repeated, while unsupervised learning allows data to be analyzed without having to define what it is that you’re looking for; identifying complex patterns and non-linear relationships within unstructured data sources. All real-time, in a matter of seconds. With reduced numbers of false positives to deal with, and no time spent re-writing business rules, the opportunities machine learning presents for compliance teams to increase efficiency cannot be understated.And perhaps even more importantly, the probability of detecting genuine instances of suspicious behavior increases massively, so organizations can more easily do their part to reduce fraud while also protecting themselves from the wrath (read: hefty fines) of the regulator.

So, stop searching. With CW360 the new standard in Transaction Monitoring is already there. And we would be happy to show you how it will make your (business) life much easier. You can book an intro with Christiaan Dappers (CEO) here.

A CW360 Intro is a short introduction to see how CW360 can help you best. We talk about the various pain points in the industry. And how CW360, including machine learning, makes you fit for the future.