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Tampa bay chapter of the acfe

CPE Lunch-n-Learn: The Fraud Fingerprint: A Visual Guide to Benford's Law

  • 27 Aug 2026
  • 12:00 PM - 1:00 PM
  • GoTo Webinar - Link will be provided

Registration

  • Dues Paying Member

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The ACFE Tampa Bay Chapter invites you to join us for our upcoming virtual Lunch-n-Learn special web series, designed to make earning continuing education credits convenient, accessible, and affordable.

Seminar: The Fraud Fingerprint: A Visual Guide to Benford's Law

https://acfetampabay.wildapricot.org/event-6799339

CPE Credit: 1 CPE

Time: August 27, 2026, 12:00 p.m. – 1:00 p.m.

Location: Virtual session via GoTo Meeting. The meeting link will be sent to registered attendees before the event.

Description:

Benford's Law has been called the "fraud fingerprint." Just as the whorls and ridges of a fingerprint can help identify an individual, the digit patterns revealed through Benford's Law can help identify a variety of issues and schemes. This session will focus on visual analysis, using case studies from multiple scenarios to demonstrate how to read Benford's Law graphs and identify signatures of avoiding limits, improper rounding, estimated figures, duplication, and more. Attendees will leave with a practical understanding of how to recognize these patterns at a glance and determine appropriate follow-up steps.

Register today to reserve your spot for this virtual Lunch-n-Learn session.

Speaker Biography:

Daniel McCarville is award-winning audit analytics professional and researcher with extensive experience applying Benford’s Law. His work focuses on practical, defensible uses of statistical analysis to identify fraud risks, anomalies, and investigative leads. He is the author of Modern Benford’s Law: State of the Art Techniques for Audit and Compliance Professionals, a practitioner-focused guide to using Benford’s Law in fraud detection, auditing, and compliance. Daniel serves as AVP of Audit Analytics, Automation, and AI at Arch Capital Group, an S&P 500 insurance company, where he leads development of data-driven risk identification and continuous monitoring capabilities.


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