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Benford's Law offers a powerful, data-driven approach to anomaly detection. Discovered 150 years ago, it wasn't until the 1990s that auditors began harnessing its potential for identifying irregularities in financial data. Today, the Benford's Law community spans a wide range of professions and academic disciplines.
Daniel J. McCarville is a recognized audit analytics professional, researcher, and speaker with more than a decade of experience developing advanced tools for auditors and compliance teams. He currently leads the audit analytics team at an S&P 500 insurance firm. His statistical expertise spans Benford's Law, machine learning, and simulation, which he applies to detect anomalies and strengthen decision-making.
His peer-reviewed research has introduced novel applications of Benford's Law and new methods for identifying irregularities in standardized test data. He has published in Emerald Open Research and received the National Legislative Program Evaluation Society's Impact Award multiple times.
Daniel has presented at major professional conferences, including IIA events, and frequently speaks at universities to inspire the next generation of data professionals. He holds a master's degree in political science from the University of Kansas, as well as Data Science from Eastern University. He also holds CIA and CRMA designations from the Institute of Internal Auditors and DASM certification from the Project Management Institute.
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