Outdated Name Recognition Tech May Compromise Marketing Efforts

Names are more than just strings of characters. Names contain critical information such as titles, gender, marital status and more. They also contain variations, such as nicknames or alternate spellings.

Because names vary from culture to culture, it has proven extremely difficult to create a single method for automatically processing them. Hispanic names have a different structure and are used differently than Chinese names. Names not written in our alphabet, such as Russian, Thai, Korean, Arabic, or Persian names, add another level of complexity, because there are multiple “standards” for transliterating them into the roman character set used by our computer systems.

Recently, corporations have recognized their poor understanding and handling of foreign names, especially those that are Arabic and Islamic in origin. Rushing to plug the gap, they consider installing additional name-matching fixes that address only these name types. They may quickly see a backlash from singling out Arab-Americans and Islamic-Americans for scrutiny.

Such accusations of “racial profiling” by their customers will cause organizations to “dumb-down” their searches in order to maintain peace. We are presented at once with the need for cultural awareness and the fear of using it to improve our systems.

One way of enforcing fair and effective compliance is by using name-recognition tools that leverage computational linguistics, software engineering and statistics to ensure an accurate evaluation of all name types. In this way, a fair and uniform approach that uses specialized techniques for the storage, retrieval and comparison of names can be used for each different type of name.

With this approach, statistics are used to determine the probable culture of a name, the probable gender of a name, variant spellings and the recognition of matches of names within a database, considering all character, cultural and phonetic variations possible.

Because this process is controlled entirely by the determination of the cultural type of the name, each different name type is handled according to techniques specifically designed for problems that are typical for that name type. Using culturally sensitive technology reduces chances of developing stereotyped responses. It ensures fair and equitable treatment with uniform software coverage of all name types.

Using empirically-driven knowledge about names creates substantial improvements in precision for name matching and name searching with reduced false positives. The availability of this new, more sophisticated name processing technology also reduces the risk of “false positives” associated with the key-based algorithms of the past. This is the type of technology used by the U.S. Intelligence and Border Protection agencies, and is now available for commercial applications.

Poorly executed name matching will frustrate users and can result in business losses due to false positives. The crucial method for examining the names of your customers against watch lists and favored-customer lists is to do so uniformly across cultures. Then, you reduce false positives while treating all customers fairly.

John C. Hermansen is the founder and chief executive officer of Language Analysis Systems, a Herndon, Va.-based maker of name-recognition software. He can be reached at [email protected].

Reproduced from National Underwriter Edition, July 14, 2003. Copyright 2003 by The National Underwriter Company in the serial publication. All rights reserved. Copyright in this article as an independent work may be held by the author.