565 Research Paper
AlmightyFluff
MOD1Reading3.pptx“Big data is NOT about the data.”
Gary King, Harvard University
“If you torture the data long enough, it will confess.”
Ronald Coase, economist
“Information is the oil of the 21st century, and analytics is the combustion engine.”
Peter Sondergaard, then Head of Research, Gartner Research
Data Analytics in Auditing
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Learning Objectives
Identify situations in which audit data analytics can be used in gathering audit evidence.
Understand the steps that are taken in performing audit data analytics.
Understand the requirements for documentation of audit data analytics.
Identify some of the tools that can be used for performing audit data analytics.
Apply data analysis techniques to client financial statement data.
Analyze output from audit data analytic techniques.
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The Auditing Data and Analytics Cycle
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Advantages of data analytics in audit
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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
PwC | Applications of data analytics in auditing
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Common Uses of Audit Data Analytics
Risk Assessment Procedures
Trend analysis of inventory costs
Preliminary three-way match testing in the revenue cycle
Accounts receivable collection periods by region
Inventory aging and days inventory in stock by item
Tests of Controls
Proper approval of purchase transactions over a threshold
Employees and Suppliers with same address
Journal entry testing by employee entry amount limits
Substantive Analytical Procedures
Predictive model of interest expense
Aging of accounts receivable
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Heat Map of Fraud Risk Factors
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Common Uses of Audit Data Analytics (cont.)
4. Tests of Details
Comparing cash collections to sales invoices and discounts
Analysis of capital expenditures vs repairs and maintenance
Detailed recalculation of depreciation using entire database and exact purchase dates
5. Procedures to help form an overall conclusion
Gross profit percentage by class of revenue
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Visualization to Assess Control Environment
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Visualization of Word Cloud – Employee Morale
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Visualizations to Assess the Market’s Perception of a New Product
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Visualizations to Assess the Market’s Perception of a New Product
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Visualizations Depicting Uncertainty around a Line Graph of Price Increase
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Conducting Audit Data Analytics (AICPA)
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Step 1: Plan the ADA
Determine the significant financial statement accounts and relevant assertions that are being tested.
Specific relevant assertion about a significant account
Determine the nature, timing, and extent of the work that will be completed as part of the ADA.
Specify the exact purpose and specific objectives of the ADA.
WCGW?
Select the techniques and tools to be used.
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Step 1: Plan the ADA (cont.)
Determine the population to be analyzed or tested, including matters which may affect the relevance and reliability of the data.
Completeness and Accuracy
System Reliability
Select the ADA that is best suited for the purpose.
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Step 2: Access and Prepare the Data
Data must be assessable and in a usable format.
Clients may store data in a variety of formats and systems, e.g. Enterprise Resource Planning (ERP) and external data repository (cloud)
Many generalized audit software tools, such as IDEA, can import from a variety of sources.
No commonly used standardized format exists, although voluntary Audit Data Standards exist.
Auditor must ensure data security and integrity.
Management may be concerned that auditor access leads to data breaches or customer confidentiality concerns.
Auditor may need to subject their systems to reliability testing.
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Step 2: Access and Prepare the Data (cont.)
Cleansing of data
Some fields may be empty, which could lead to errors in analysis.
Date fields may have numbers or letters.
Data may be outside relevant date range.
Format of dates may vary (D-M-Y vs M-D-Y vs Y-M-D).
Country-specific differences, such as currency ($1.22 vs 1,22E)
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Step 3: Consider the Relevance and Reliability of the Data Used
The auditor must consider whether the data has a logical connection to the purpose of the audit procedure and the assertion being tested.
What data would be most relevant to performing the ADA?
Is the data considered most relevant available?
If not, are there alternative ways to obtain the data? Alternative data that could be used?
Similarly, auditors must evaluate the reliability of any data used in ADA.
Source reliability
Nature and relevance of information available
Internal controls over data preparation
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Step 3: Consider the Relevance and Reliability of the Data Used (cont.)
Completeness and Accuracy of data must be ensured.
Reliability of accounting systems and Information Technology General Controls (ITGCs) must be tested prior to using data from a client system.
To determine the reliability of data, the auditor may consider
Whether the ADA is a risk assessment procedure, a test of controls, etc.
The risk assessment associated with the account/assertion
The extent of other audit procedures
The nature and source of data (e.g. internal vs. external)
The process used to produce the data
Additional procedures to ensure data reliability
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Step 3: Consider the Relevance and Reliability of the Data Used (cont.)
Characteristics of data that may affect relevance and reliability
Nature (e.g. financial vs. non-financial, historic, time-sensitive, economic, etc.)
Source (controlled by accounting department, controlled internally but outside accounting department, external)
Format (numerical, text, fixed fields, unstructured)
Timing (point in time or period of time, rate of change)
Extent (volume and variety of subject matter/sources)
Level of Aggregation (account balance vs. transaction, annual vs. hourly, consolidated vs. segment)
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Characteristics of Data
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Step 4: Perform the ADA
Actual performance of the ADA varies greatly depending on the purpose of the ADA.
If initial results indicate ADA needs to be revised, consider revisions and reperformance.
If the ADA has been properly designed and performed, consider additional procedures on identified items that warrant further attention.
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Step 5: Evaluate the Results and Conclude
Have the objectives of the ADA been achieved?
If not, plan and perform different procedures.
Gather additional evidence to help reduce risk of material misstatement; design and perform procedures on notable items.
Duplicate items.
Missing items.
Items with higher assessed risk.
Address risk of material misstatement for remaining population items.
Consider whether risk of material misstatement exists in items not identified as notable.
It may be appropriate for auditor to conclude that no additional risk of material misstatement is present.
Document work performed.
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Documentation Requirements
AU-C 230 applies to ALL audit documentation, including ADA.
Documentation should be prepared to be sufficient such that an experienced auditor, with no prior connection with the engagement can understand:
Nature, timing and extent of procedures performed
Results of procedures and evidence obtained
Conclusions reached and significant judgments made
The auditor should record:
Identifying characteristics of specific items or matters tested
Who performed the work and date of performance
Who reviewed the work, date of review, and extent of review
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Documentation Requirements (cont.)
Auditor may record the scope of the procedure and population analyzed.
No requirement to include the data analyzed (generally impractical)
Possible documentation specific to ADA:
Objectives of the procedure
Risks of material misstatements addressed at the financial statement or assertion level
Sources of the data and how it was determined to be sufficient and appropriate (complete and accurate)
The nature of the ADA and the tools and techniques used
Tables or graphics used, including how they were generated
Steps taken to access data, including the system accessed and how the data were extracted and transformed
Evaluation of matters identified as a result of applying the ADA and actions taken
Identifying characteristics of specific items or matters tested
Preparer and reviewer information as required by AU-C 230
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Documentation Requirements (cont.)
Screenshots of graphics generated in performing an ADA may be included in documentation.
Only graphics necessary to support the auditor’s work and conclusions should be included.
The auditor need not document every matter considered or professional judgment made.
All misstatements identified other than those considered clearly trivial should be documented.
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Common Tools Used in ADA
Generalized Audit Software
IDEA
ACL
Data Preparation and Statistical Analysis Tools
Alteryx
R
SAS
Python
Visualization Tools
Tableau
Microsoft Power BI
All-Purpose Tools
Excel
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Professional Skepticism in ADA
An auditor must plan and perform an audit with professional skepticism, and must exercise professional judgement.
Some areas where professional skepticism and judgment apply in ADA:
Assessing the completeness and accuracy of client data
Making assumptions in planning the procedures and evaluating the results
Considering unusual circumstances
Appropriately generalizing in drawing conclusions
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