One of the most important tasks any compliance officer should complete is the risk assessment of both customers and their transactions.
For these tasks there are a number of different activities they can do, such as 'data validation', 'name screening', 'data analytics' and 'profiling'
These processes can be done manually, but are lengthy. For the modern financial services provider, the speed of executing these activities are crucial.
They need fast and reliable systems, true positive alerts only, and an automated systematic alert management procedure to complete their risk assessment, in order to decide if further actions are required.
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In conclusion Idetect states that the majority of automated name matching systems employ legacy matching algorithms. This has made it difficult for compliance officers to make decisions and take actions on the information available.
The implementation of Machine Learning in a new generation of name matching systems increases the number of compared features, resulting in a deeper match.