How do we detect the unknowns? Sound familiar? When it comes to Financial Crime Analytics, there is always a risk of missing what you don’t know, leaving the dangling fear of drifting away from the truth with what you’ve already seen. What are the techniques that can be used to detect unknown and stay one step ahead of the criminals?
Leverage Unsupervised Machine Learning (UML) techniques: UML is not limited by existing knowledge, with the appropriate hypotheses, unknown trends can be detected with simple clustering or self-organizing algorithms.
Apply data labelling techniques to increase the granularity of your feedback loop: when it comes to investigation procedures, free text often is discouraged, however, with the help of Natural Language Processing (NLP) techniques, label your alert and investigation results with as much information as possible to allow extra insights to be gained.
Always conduct Below-the-Line analysis (BTL): have a methodology to define your “lines” and always apply risk-based sampling techniques to look at BTL events, establish a procedure to handle BTL event findings and follow it regularly.
Linkage analysis to look across functions: combine your Fraud, Sanction and AML data, combine your Transaction Monitoring investigation results with complicated case investigation results, the more data you analyze, the more “unknowns” become known.
Review analytics evidence using independent reviewers: leverage consultants, your second line defence IMR (Independent Model Review) functions, or your IA (Internal Audit) functions to provide an objective view.
Analytics doesn’t have to be complicated, simple techniques can go a long way when employed and enforced regularly. Contact us for further discussion on how we can help to tailor some of the above techniques for your needs.
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