Organizations across government and industry are faced with the complexity of matching the names of individuals and businesses across diverse, multilingual sources in high-volume and high-velocity data environments. The consequences of name matching failure can be severe, especially in critical use cases, such as border crossings, counter-terrorism, crimefighting, financial compliance, payment verification, and customer/patient identification and records linking.
Rosette® Name Indexer by Babel Street is an AI-powered solution for use by government and commercial organizations whose risk and identity operations depend on correctly screening names. With advanced algorithms to accurately match names across multiple languages, scripts, and cultural variations, Rosette reduces false positives and negatives with intelligent name, address, and date matching.
This technical brief explores the challenges of achieving accurate name matching and how Rosette Name Indexer intelligently fuzzy matches names, addresses and dates across languages and cultures through a patented two-pass process.
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