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Designing Anti-Fraud Tests that (Actually) Work!

Format: Online

While data analytics is not a new concept, many organizations have tried (many unsuccessfully) to create data analytics that deliver meaningful results and insights, monitor internal controls and identify fraud. This session will focus on how to correlate data and design anti-fraud tests using a risk-based approach in order to tell a story that is both compelling and insightful. An automated anti-fraud journal entry testing model will be demonstrated for the group, as well.

DATE: July 9, 2024
TIME: 12:00 PM-1:00 PM ET

One (1) NASBA CPE will only be awarded to participants on the live broadcast who are logged in for a minimum of 50 minutes and engage on at least three poll questions per each hour of the event.

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Matt Storlie, CFE, CIDA

With 30 years of experience in business and accounting, fraud examinations, data analysis, internal audit, and IT systems, Matt Storlie assists clients with forensic services, internal investigations, computer forensics, e-discovery and litigation readiness, and fraud risk assessments. As one of the firm’s subject matter experts on data analytics, he utilizes his deep experience with IT systems, internal controls, and data analytics to develop proactive, risk-based anti-fraud models and programs, and is a certified data analyst of IDEA® software.

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