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. Audit teams frequently face questions like: How do we expand the number of audits this year and ensure a quality deliverable without increasing staff or budget? How do we do more with less?  These demands require us to challenge our audit techniques and begin to leverage technology in our controls testing. With shrinking budgets and limited resources, this can be an overwhelming challenge for any internal audit function.


In this hands-on (not theory!) workshop, participants will use one of the leading data analytics tools to perform real controls testing while learning to design a continuous audit from scratch without having to be a programmer.  We will take a common manual test performed the same way for years in most organizations and learn to automate it. Participants will perform all the required steps to fully automate the process and create a continuous audit. You’ll complete the course having created a continuous audit that runs when needed.  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


  • 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
  • Creating continuous monitoring vs. auditing
  • Documentation standards | 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





Who Should Attend




Advanced Preparation

2 Days





Internal auditor staff and management with data analytics experience; financial and operational management and staff with data analytics experience

Automating Data Analytics course or equivalent experience