Objectives - Blackburn, Childers & Steagall, CPAs · Objectives • Learn valuable computer...
Transcript of Objectives - Blackburn, Childers & Steagall, CPAs · Objectives • Learn valuable computer...
5/16/2016
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Chad Kisner, CPA, CISA, CITP
Objectives
• Learn valuable computer assisted auditing tools and techniques (CAATTs) to take back to your firm. These techniques include analysis of high‐risk audit areas such as those associated with fraud risks.
• Learn how to leverage the AICPA Audit Data Standards and CAAT applications available in the marketplace to streamline audit processes.
• Learn about techniques and tools, practical application of techniques in common risk areas and focused analyses and findings.
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Agenda• CAATs
• Definitions/Overview
• Audit Data Standards
• Discussion of Tests and Testing Ideas
What are CAATs?
• Tools• Packages designed for data analysis
• Database queries, report writers
• Spreadsheets
• Techniques• Manipulate data
• Analyze data from different sources
• Compare financial and non‐financial data
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AICPA Publications
• Evolution of Auditing: From the Traditional Approach to the Future Audit – November 2012
• Reimagining Auditing in a Wired World –August 2014
• See last page of this presentation for live links
CAATs & Substantive Procedures
• These can replace and/or supplement traditional substantive procedures• Allows the auditor to analyze 100% instead of sample
• Provides stratification/statistical analysis and improved sample selection
• Understanding related activities can help identify value added CAAT tests.
• Requirements• Integrity of Data
• Normalization of Data
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Consideration of Fraud –AU‐C Section 240
• The auditor should ordinarily presume that there is a risk of material misstatement due to fraud relating to revenue recognition AU‐C Section 240 provides examples of procedures to address risk of fraud related to revenue recognition• Substantive analytical procedures relating to revenue using disaggregated data
• Computer‐assisted audit techniques
• Discussions with personnel outside of finance
• Physical observation of sales cut‐off
• Testing controls
• AICPA –AU‐C Section 240 link to PDF on last page
What are Data Analytics?
• Data Analysis is defined as the process of looking at and summarizing data with the intent to extract useful information and develop conclusions. It employs various technologies and programming techniques
• Benefits of Data Analytics• Identify anomalies, patterns and indicators of risk
• Analyze large populations of data instead of samples
• Analyze data from disparate datasets, multiple systems or locations
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Phases of Data Analytics
• Acquire the Data
• Transformation and Standardization
• Management
• Analysis
• Reporting
Data Acquisition
• Types of client data that are acquired:• Invoices
• Journal Entries
• Employee Records
• Vendor Information
• Customer Information
• Acquire client’s data from multiple locations and/or systems
• Acquire client’s data from various media types and file formats
• Acquire large volumes of data
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Data Transformation & Standardization
• Standardize data from multiple systems
• Types of data needing transformation or standardization:• Names and addresses
• Date conversion
• Currency conversion
• Customer codes
Data Management
• Tools used to import, validate and analyze data• IDEA
• ACL
• Active Data for Excel
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Data Analysis
• Identify patterns of fraud• Vendors consistently at or just below signatory limit
• Payment of duplicate invoices
• Round dollar transactions
• Ghost employee analysis, including SSN comparison
• Conduct trend analysis• Change in vendors/amount spent with vendors over time
• Identify data anomalies• Manual journal entries made after 11:00 pm or on holidays
• Understand results• Iterative process, providing additional information when needed
Reports
• Reconciliations• Reconcile general ledger activity to trial balances
• Payroll• Compare the outstanding check list to bank statements
• Customers• Analyze A/R credits per customer
• Vendors• Analyze vendors and costs
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Overview of the Audit Data Standards
Challenges• One of the challenges that management and auditors continue to face is obtaining accurate and usable data in a format following a repeatable process. This is why the AICPA’s Assurance Services Executive Committee’s Emerging Assurance Technologies Task Force seeks to increase audit efficiency by developing voluntary, uniform audit data standards.
• These Data Standards are being designed to assist primarily with:• Data Acquisition
• Data Transformation and Standardization
• Data Analysis – audit apps
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Benefits of Audit Data Standards
• Standard set of company data available on demand
• Drill down and identify higher risk areas
• Standardize analyses across business units with different reporting systems in place
• Better evaluate key metrics in order to substantively predict company performance
• Analyze growth opportunities
• Search for questionable transactions
Discussion of Tests & Testing Ideas
General Ledger1. Suspicious weekend or holiday journal entries
2. Duplicate journal entries: same account, same amount
3. GL period close cut‐off
4. Segregation of duties: Parked vs. Posted
5. New GL accounts
6. No change balance sheet accounts
7. Segregation of duties: Poster vs. Creator of JE
8. Even dollar JE amounts
9. Split entry JE over approval limit
10. Authorized user changes
11. Outstanding JE to suspense accounts
12. GL period close: Period re‐opened
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Discussion of Tests & Testing IdeasSales/Revenue/Receivables
1. Duplicate invoices
2. Excessive write‐offs
3. Unauthorized adjustments
4. Manual discounts
5. A/R aging
6. Critical period sales volume
7. Duplicate / ghost customers
8. Excessive refunds
9. Incorrect sales price
10. Credit memos vs A/R
11. Excessive unauthorized discounts
12. Segregation of duties: updating v. approving credit limits
13. Unauthorized price changes
Discussion of Tests & Testing IdeasPurchase Cards
1. Top 15 spenders
2. Phantom merchants
3. High transaction volume
4. Duplicate cards
5. Keyword testing
6. Split purchases
7. Inactive employees
8. Round amounts
9. T & E and Pcard match
10. Dormant cards
11. Suspicious MCC / SIC codes
12. Excessive recognition & appreciation expenses
13. Expenses processed without receipts
14. Large transactions
15. Suspicious weekend or holiday purchases
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Discussion of Tests & Testing Ideas
Travel & Entertainment1. Airlines: ticket analysis
2. Travel claims & vacation analysis
3. Excessive meal expenses by location
4. Excessive personal payments
Discussion of Tests & Testing IdeasPayroll
1. Unusual employee master file changes
2. Excessive overtime
3. Phantom (ghost) employee
4. Duplicate employees
5. Payments after termination
6. Minimal vacation time used
7. Excessive days off
8. Multiple salary increases
9. Frequent employee master file changes
10. Active employees with no YTD earnings
11. Gross earnings over threshold
12. Unusual bonus increase
13. Unauthorized paid overtime
14. Serial vacationers
15. Missing or invalid employee data
16. Excessive hours
Evolution of Auditing: From the Traditional Approach to the Future Audit – November 2012 https://www.aicpa.org/interestareas/frc/assuranceadvisoryservices/downloadabledocuments/whitepaper_evolution-of-auditing.pdf Reimagining Auditing in a Wired World https://www.aicpa.org/InterestAreas/FRC/AssuranceAdvisoryServices/DownloadableDocuments/Whitepaper_Blue_Sky_Scenario-Pinkbook.pdf AICPA AU-C-240 https://www.aicpa.org/Research/Standards/AuditAttest/DownloadableDocuments/AU-C-00240.pdf Data Management: IDEA - https://www.audimation.com/Product-Detail/CaseWare-IDEA ACL - http://www.acl.com/ Active Data for Excel - http://www.informationactive.com/ AICPA Audit Data Standards Resource Page https://www.aicpa.org/interestareas/frc/assuranceadvisoryservices/pages/auditdatastandards.aspx