{"id":9171,"date":"2021-05-26T15:33:59","date_gmt":"2021-05-26T13:33:59","guid":{"rendered":"https:\/\/compliance-wise.com\/?p=9171"},"modified":"2025-06-13T12:03:16","modified_gmt":"2025-06-13T10:03:16","slug":"the-call-for-a-new-approach-of-transaction-monitoring","status":"publish","type":"post","link":"https:\/\/compliance-wise.com\/en\/the-call-for-a-new-approach-of-transaction-monitoring\/","title":{"rendered":"The call for a new approach of Transaction Monitoring is fierce. But actually, the new approach is already there."},"content":{"rendered":"\t\t
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Love it, hate it, or just don\u2019t understand it, Machine Learning and AI technology is here to stay. And in the world of compliance tooling, this is very good news.\u00a0 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\u2019s going to be inescapable. That\u2019s why we built CW360, our premium SAAS solution, including Transaction Monitoring and Know Your Clients (KYC), for banks and Financial Institutions.<\/p>

Rule-based vs Machine Learning <\/strong><\/p>

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\u2019t process the vast and real-time data streams critical for the digital space.<\/p>

Enter the world of CW360, of AI and Machine Learning. Offering the chance to get insights into financial behaviors in ways that probably can\u2019t 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.<\/p>