Use Case

Continuous Monitoring and Audit

 

As auditing teams scramble for the time and resources to do their job, PCAOB guidance is moving towards continuous monitoring and auditing to assess important controls more frequently. Analytics provides the continuous monitoring and auditing needed to evaluate increasingly complex transactions, ensure compliance, and keep up with growing volumes of data.

Efficiency Gains

Automatically assess 100% of the population for key control testing

Bottom-Line Returns

Optimize continuous audit without huge operational investment

Risk Reduction

Ensure audit accuracy easily and quickly

 

Business Problem

How do you choose what to monitor and audit? With limited resources, you know you can’t examine every transaction and control, so you have to make yes-or-no decisions about the data you sample. How do you establish guidance for what to audit? How do you ensure that your auditors follow it? Your organization relies on you to help ensure compliance, but you’re bound by sampling techniques that haven’t kept pace with new kinds and increasing volumes of data. Public Company Accounting Oversight Board (PCAOB) guidance is moving closer to continuous monitoring and continuous auditing, which allows for assessing important controls more frequently. But based on completely manual processes, your decisions about which data to sample are introducing risk to a process that’s supposed to reduce it.

Alteryx Solution

Analytics automation makes continuous monitoring and auditing possible by automating the entire testing of an important control, evaluating 100% of the population. Continuous monitoring meets the needs of management, helping them keep an eye on business processes and adjust them where necessary. Continuous auditing enables compliance officers and auditing teams to gather and evaluate diverse data types in large volumes on an ongoing basis.

When audit departments go from sampling to total testing, they reduce risk and get a picture of all underlying activity. Not only can analysts harvest more useful findings, but they can also focus on results rather than on making yes-or-no decisions about the data to sample.

 

Additional Resources

 
 
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Starter Kit for Predictive Analytics
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Customer Stories

 
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