Name Matching & Revision (Part 2)

In the first part, we characterized the name matching problem. In this second part, we will discuss false negatives. According to article 13 of AMLO-FINMA, financial intermediaries must develop criteria to identify higher-risk business relationships. The dispatch regarding the revised AMLA mentions that the risk-based approach is systematically anchored in the FATF standards. Legislators therefore correctly assume that a certain latitude is available when it comes to recognizing risky customer relationships. In this gray zone, there’s no such thing as a 100% perfect decision. Nevertheless, it is necessary for the risk of false negatives to be kept as small as possible.

Possible causes of false negatives include:

  • Differing interpretation of PEPs
  • Name variants not recognized by the match profile
  • Missing profiles
  • Profiles with insufficient information
  • Too many hits that cannot be verified with the available resources
  • Incorrect text encoding
  • Form of address and/or academic title in name (Dr. Peter Example)
  • Incorrect data capture (e.g. Verena or Hans as first names)
  • Communities of heirs as natural persons
  • Nicknames in place of official first names (e.g. Bill instead of William, Fritz instead of Friedrich)

Complete Revision of the Federal Data Protection Act

Complete Revision of the Federal Data Protection Act: „As of 15th September 2017, draft and report for a completely revised Federal Data Protection Act is public. In a first step parliament and the people agreed to adaptations in order to be compliant with EU law. The second part of the revision is debated by the parliament since September 2019. Data Protection is to be increased by giving people more control over their private data as well as reinforcing transparency regarding the handling of confidential data.”


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