Entity Resolution and Fuzzy Matching
June 17, 2015
ENTITY RESOLUTION and FUZZY MATCHING
Entity Resolution and Fuzzy Matching software can be quite expensive! ($1 Million!).. then, typically you have to hire a consultant to come in and configure and run the off-the-shelf software for you to achieve the kind of results you want. At Automated Auditors, LLC, our Entity Resolution and Fuzzy Matching software is offered as a customized service to you. The goal is to get the most out of your data. Your goal may be to reconcile disparate data sources, or to find hidden relationships between vendors and employees. Here are some examples where our fuzzy matching and entity resolution algorithms have been very useful:
1) Reconciling the List of Excluded Individuals and Entities (Medicare) with Medicare Providers, via fuzzy name and address matching.
2) Consolidating city names and mailing addresses for Customs and Border Protection (CBP).
3) Reconciling financial data against the Terrorist Watch List using fuzzy name matching.
4) Conducting a full vendor file clean-up and master data management for The World Bank.
5) Reconstructing Accounts Receivable files to join them together by student name, due the lack of a common identifier.
Our fuzzy matching algorithms are currently being utilized to merge Medicaid and Medicare providers and beneficiaries. With millions of providers and beneficiaries, this is no small task. Both the fuzzy matching and entity resolution algorithms are proving to be useful in combining Medicaid data with Medicare data in an accurate and systematic way.
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