www.pwc.com Applications of data analytics in

Transcript:www.pwc.com Applications of data analytics in:
www.pwc.com Applications of data analytics in auditing 1 Course contents Overview Key areas of application 2a Internal controls 2b Substantive testing 2c Risk assessment Case study Questions 2 Overview The right mix of mind and machine can help reduce the impact of human bias and yield more accurate answers, even for complex problems. 3 http://www.pwc.com/us/en/advisory-services/data-possibilities/big-decision-survey.html Learning objectives At the end of this section, students will be able to– Explain the role data analytics has in the external audit Outline the criteria used to gauge potential analytics candidates Identify common pitfalls that can undermine a successful audit 4 Advantages of data analytics in audit How can data analytics create advantages for external audit work? 5 Advantages of data analytics in audit 6 Customization Tailor the analytics solutions to support client needs (e.g. journal entry testing) Predictability Ability to replicate processes across type of work and client engagements Test Size Provides ability to test entire population instead of a sample Data Insight Visualization and analytics tools allow for a better view of the data and pinpoints areas of interest for auditors Efficiency Performance of data analytics maximizes time spent structuring data into information Framework for selecting analytics–enabled audit(s) 7 Data availability & complexity Availability: Is data available for the process in an easy to access and use format? Start Not a likely analytics candidate Potential analytics candidate Strong analytics candidate ? Framework for selecting analytics–enabled audit(s) (continued) 8 Availability: Is data available for the process in an easy to access and use format? Complexity: Are there multiple sources? Is the data able to be validated for consistency and completeness? No Yes Start Not a likely analytics candidate Potential analytics candidate Strong analytics candidate Framework for selecting analytics–enabled audit(s) (continued) 9 Availability: Is data available for the process in an easy to access and use format? Familiarity: Does the team have knowledge of the business process to understand the risks and data? Complexity: Are there multiple sources? Is the data able to be validated for consistency and completeness? No No Yes Yes Start Not a likely analytics candidate Potential analytics candidate Strong analytics candidate Framework for selecting analytics–enabled audit(s) (continued) 10 Availability: Is data available for the process in an easy to access and use format? Repeatability: Does the area represent a common audit focus areas that would repeat in the future? Familiarity: Does the team have knowledge of the business process to