Fraud detection is an important concern for both commercial and public sector organizations. On the commercial side, banks, insurers, and practically all commercial organizations strive to avoid the financial losses and the potential negative publicity associated with fraud. On the public side, government agencies must ensure that public services and programs (e.g., visa applications, asylum requests, healthcare programs) are not abused for personal gain or, worse, with the intent to inflict harm on others. On both sides, organizations strive to keep up with and thwart new, elaborate fraud schemes.
It is therefore critical to be able to count with advanced and robust technology that can reveal matches with imperfect or partial information. NetOwl’s matching technology, the winner of the MITRE Multicultural Name Matching Challenge, has been designed to discover matches despite discrepancies (e.g., transliteration variants of foreign names, name order variation, tokenization variation, misspellings) and also indirectly via associations (e.g., permits for a person affiliated with a barred organization, insurance claims for services rendered by a blacklisted provider, visa applications tied to a fraudulent preparer).
In fact, NetOwl’s matching technology is widely used for fraud detection. For example, Blackhawk Engagement, a large provider of manufacturer and retailer promotional marketing programs, is using NetOwl NameMatcher to automatically provide a candidate list of possible matches for a given name. This enables Blackhawk Engagement to protect against fraudulent, multiple submissions of rebate requests and other customer incentives.