Name matching is critical when it comes to terrorism watch lists and those involved in screening customers against watch lists like OFAC. Inaccurate name screening can lead to significant fines and risks to the business. Some cases have included PayPal, TransUnion, and the National Bank of Pakistan. But there are areas beyond counter-terrorism where fuzzy Name Matching is a critical technology, such as Homeland Security and the financial, healthcare, retail, and background screening industries. Traditional fuzzy name matching methods have included dictionary lookup, Soundex, edit distance, and rule-based, but the latest approach uses a machine-learning algorithm and large-scale, real-world, multi-ethnicity name variant data to learn a collection of intelligent, probabilistic name matching rules from the data.
