How Analytics Should Be Used in Controls Testing Rather Than Sampling
Sampling has existed as a standard for controls testing since controls testing began. We’ve developed algorithms to tell us how many samples we should pull and how many errors we can have and still pass the control. We’ve even developed algorithms to tell us how many more samples we can test if the control didn’t pass the first time. Most controls analytics do not require a degree in data science, but they do require the controls team begin changing its behaviors. Join us to understand what it takes to begin this change, it’s not as challenging as you might think.
- Understanding the advantages of analytics vs sampling
- How to Identify controls where analytics can be applied
- Real-life examples of controls and their associated analytics
- How to effect a change