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I'm wrapping up Prof. Andrew Ng's excellent five-course specialization on Deep Learning and am now looking for how I might apply machine learning to screening names against digital watchlists such as OFAC's SDN or Consolidated Sanctions List. I currently have a solution that uses Metaphone 3 and a normalized Levenshtein Edit Distance, but I would love to find some research papers that might show how I could build a Machine Learning solution to this problem to see if I can reduce false positives without significantly increasing the risk of false negatives.

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