Verification of Payee: what makes name matching so complex?

This check mainly consists of a matching process between the provided name and the stored account holder name. Such checks may sound simple, but you can find many complexities if you look closer. The following list of challenges shows why it is necessary to establish a set of sophisticated algorithms to achieve reliable and correct results.

• Variations in spelling: Names can be spelled differently due to typos, misspellings, or variations in transliteration, especially in multicultural or multilingual contexts.
• Aliases, titles, and nicknames: People often have official titles like “Dr.” or use aliases/ nicknames that may not be directly related to their legal names, complicating the matching process.
• Cultural differences: Cultural naming conventions vary widely, leading to challenges in matching names across diverse cultures. For example, the order of given names and surnames varies between Western and Eastern cultures.
• Missing, incorrect or incomplete data: Incomplete, missing, incorrect or outdated records, duplicates, and inconsistencies can make it difficult to accurately match names.
• Homographs: Names that are spelled the same but have different pronunciations or meanings (homographs) can lead to confusion and inaccurate matches.
• Contextual ambiguity: Names may have different meanings or refer to different entities depending on the context. For example, the name "John Smith" could refer to multiple individuals, making it difficult to accurately match without additional context.
• Cultural biases: Name matching systems may inadvertently exhibit biases towards certain names or cultural backgrounds, leading to disparities or inaccuracies in matching results.
• Name changes: Individuals may change their names due to marriage, divorce, or other life events, resulting in multiple names associated with the same person.

In addition to the challenges for individual names (person), the matching of company names presents the following challenges:

• Abbreviations and Acronyms: Companies often use abbreviations or acronyms in their names, leading to discrepancies in how their names are represented. For example, "International Business Machines Corporation" may be abbreviated as "IBM," "I.B.M. Corp.," or "International Business Machines Corp.," complicating the matching process.
• Aliases and Trade Names: Companies may operate under different trade names or aliases, further complicating the matching process. For example, a company may be legally registered under one name but commonly known by a different name.
• Company Mergers and Acquisitions: Mergers, acquisitions, and rebranding efforts can result in changes to company names or the creation of new entities. Matching company names accurately requires keeping track of these changes and maintaining up-to-date databases.
• Internationalization and Localization: Companies operating internationally may have different names in various languages or regions. This adds complexity to the matching process, especially when dealing with multilingual datasets.
• Legal Entity Types: Different legal entity types, such as corporations, partnerships, and sole proprietorships, may have distinct naming conventions or suffixes. Matching company names accurately requires understanding these conventions and considering them during the matching process.

PSPs will need to be able to manage these types of complexities to have reliable IBAN-Name matching capabilities. Some of these obstacles could be solved by activities like data cleaning or usage of additional data sources (like nickname list or corporate directory), others will need a more advanced approached like the usage of Artificial Intelligence.

In any case the success of the Verification of Payee service in reducing the upcoming fraud highly depends on the quality of the underlying matching algorithms. Learn more about Instant Payments and Verification of Payee. Discover all our solutions for Financial Institutions.