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.
DESIGNED FOR
This course is ideal for internal auditors, compliance professionals, risk managers, and anyone involved in auditing or governing AI initiatives within an organization.
BENEFITS
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.
HIGHLIGHTS
Date(s) and Time: Jul 9 from 12:00 PM - 1:00 PM ET
In this session, participants will:
- Examine historical data analytics methodologies and techniques.
- Explore data correlation and how to develop a risk-based approach.
- Discover how a risk-based approach could benefit your organization.
- Witness a demo of an automated anti-fraud journal entry testing model.
PREREQUISITES
None
ADVANCE PREPARATION
None