Developing Effective Continuous Audits

• Importance of planning objectives
• Determining the level of effort for each of the four stages of data analytics progression
• Learning how to execute a data discovery walkthrough
• Designing a continuous audit from a manual test based on a sampling approach
• Developing new tests to support control objectives
• Learning how to transition to continuous

CONTENT

Overview of Data Analytics

• What is data analytics?
• CAATs vs. continuous auditing vs. continuous monitoring
• Why data analytics
• Data analytics uses in internal audit, in business
• Automation
• Implementation process overview

Variables

• Overview
• System-generated vs. user-created
• Leveraging variables for continuous auditing

Case Study | Planning

• Understanding the sample testing procedures
• Conducting a data discovery interview
• Brainstorming new tests
• Documenting clear objectives

Case Study | Preparation

• Data access and validation
• Identifying data integrity issues
• Determining critical fields to meet objectives
• Control totals vs. reconciliation

Case Study | Testing

• Reviewing data for additional tests
• Preforming tests

Case Study | Review

• Compare before analytics vs. after analytics
• Documentation standards
• Creating continuous monitoring vs. auditing
• Future considerations

FOR WHOM

Internal, financial, operational, and risk management and staff with analytics experience

TRAINING METHODOLOGY

The training methodology combines lectures, discussions, group exercises and illustrations. Participants will gain both theoretical and practical knowledge of the topics. The emphasis is on the practical application of the topics and as a result participant will go back to the workplace with both the ability and the confidence to apply the techniques learned to their duties.