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This paper describes the development of a scalable social network discovery algorithm and its deployment in a revenue agency. A revenue agency makes many risk assessments in the course of its operations. Registration of companies, individuals and other entities need to be checked to avoid fraudulent registrations or identity theft. Correct lodgement or filing of returns, correct reporting of income, expenses and other relevant data on the return and finally payment of any resulting liabilities all involve risk assessments and prioritization of work. Most current risk assessments are made on the basic of the particular entity history or current return details. These risk assessments do not exploit social, professional and organizational relationship. The application of social network mining extends the current risk models to take into account an entity's relationships to other entities.