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Data Analytics: Elevating Internal Audit’s Value

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The sheer mass of data available to today’s internal auditors requires a systematic approach.

This research-based report provides the tools you’ll need to become more efficient in your data mining efforts.

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New from The IIA Research Foundation!

Today’s audit leader struggles with creating in integrated, efficient approach to data mining that maximizes the impact and value the audit department delivers.

Data Analytics: Elevating Internal Audit's Value is the result of a research project that aimed to lead to the design of a data analytics framework to help internal audit functions. It covers a wide spectrum of concepts, such as:

  • Financial risk.
  • Compliance.
  • Fraud.

The framework helps internal audit to broaden risk coverage and enhance audit efficiencies.

You will learn how to:

  • Develop a data analytics framework and use it to accomplish multiple audit objectives.
  • Enhance internal audit efficiency through the use of data mining and analytics.
  • Eliminate duplicated data mining and analysis efforts across audit and other functions.
  • Determine the optimal effort needed to maximize the framework.

The IIA Research Foundation, in partnership with Grant Thornton, conducted research and provided subject matter experts and editorial resources to produce this report.

 

Item Number: 10.5074

New from The IIA Research Foundation!

Today’s audit leader struggles with creating in integrated, efficient approach to data mining that maximizes the impact and value the audit department delivers.

Data Analytics: Elevating Internal Audit's Value is the result of a research project that aimed to lead to the design of a data analytics framework to help internal audit functions. It covers a wide spectrum of concepts, such as:

  • Financial risk.
  • Compliance.
  • Fraud.

The framework helps internal audit to broaden risk coverage and enhance audit efficiencies.

You will learn how to:

  • Develop a data analytics framework and use it to accomplish multiple audit objectives.
  • Enhance internal audit efficiency through the use of data mining and analytics.
  • Eliminate duplicated data mining and analysis efforts across audit and other functions.
  • Determine the optimal effort needed to maximize the framework.

The IIA Research Foundation, in partnership with Grant Thornton, conducted research and provided subject matter experts and editorial resources to produce this report.

 

Item Number: 10.5074