In this five-day seminar, you will learn everything you need to know about effectively integrating data analytics, or CAATs (Computer Assisted Audit Techniques), into your internal audit processes. You will learn how technology can be used to more efficiently and effectively achieve desired audit results, and get a chance to brainstorm analytics across most major business cycles.
As the course progresses, you will quickly progress from understanding basic analytic techniques such as stratifications, summarizations, duplicate identification, into more advanced techniques such as fuzzy matching, Benford’s Law, and statistical and regression analysis. You will also get a chance to explore cutting-edge topics such as visual analytics, risk scoring, and spatial analysis. Regardless of the tool you currently use or plan to use in your department — whether generic like MS Excel or MS Access, audit-centric like ACL or IDEA, or more IT-oriented like SQL or SAS --the standard pseudo-code used throughout the course will allow you to easily take what you have learned and quickly code it in your tool of choice. If you bring your own laptop, you’ll even be able to practice the techniques on real data files using your tool of choice.
Later in the week, you will learn how to progress from basic data analysis into a fully automated/repetitive mode and learn the fundamentals of Continuous Auditing. You will review common hurdles and hear how the most successful organizations in the world have been able to exploit the power of data analysis to achieve visible and sustainable value.
Participants in audit management will learn how to design effective strategies and programs to ensure sustainable results. Those who will be more hands-on in your analytics program will get a chance to work on real-world scenarios with sample data files. Whether you are in audit management (directing a team where you yourself may never personally use the technology) or the person who will ultimately be using the performing data analysts, this course is for you.