Course Description
The ever-increasing demand on Internal Audit to deliver more—detailed risk assessments, fraud detection and investigation, performance auditing, root cause analysis, and more—often without increased staffing or budget can put tremendous pressure on the audit team.
These demands require us to challenge our audit techniques and begin to leverage technology in our controls testing.
In this hands-on (not theory!) workshop, you will use one of the leading data analytics tools to perform real control testing while learning how to design a continuous audit from scratch without having to be a programmer. We will take a commonly performed manual test and learn to automate it. Through a hands-on experience, you will perform all the required steps using a proper data analytics tool to fully automate the process and create a continuous audit. You’ll complete the course having created a continuous audit that runs when your organization needs it to.
In this hands-on course you will work through exercises in actual data analytics tools in addition to lecture and live demonstrations. It is recommended that attendees should bring laptops (with the ability to install software, or the software already installed) to class to participate in the hands-on exercises.
BONUS: ALL REGISTERED ATTENDEES WILL RECEIVE A TRIAL VERSION OF THE SOFTWARE AND BEST PRACTICE TEMPLATES.
Learning Objectives
- 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 monitoring
- Documenting your work without words
Course Outline
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
Case Study | Data Analytics Progression
- Create analytics for each of the 4 stages
- Create automated:
- Standardized reports
- Supporting documentation
- Develop a library of utilities for use with other continuous audits
- Importance of a development environment vs. a production environment
Additional Information
Who Should Attend
Internal, financial, operational, and risk management and staff with analytics experience
Learning Level
Advanced
Delivery
Group-Live
Field
Auditing
Advanced Preparation
None
Recommended Prerequisites
Fundamentals of Data Analytics or equivalent
Session Duration
On Site: 2 days
CPE Credits: 16