Connections 2013 change your thinking - integrating analytics into the audit process final

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© ACL Services Ltd.
© ACL Services Ltd.
Jim Kaplan CIA CFE
AuditNet LLC
Richard Lanza CPA
Cash Recovery Partners LLC
ACL Connections 2013
Change Your Thinking - Integrating
Analytics into the Audit Process

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3© ACL Services Ltd.ACL | Connections 2013
 President and Founder of
AuditNet®, the global resource
for auditors
 Auditor, Web Site Guru,
Internet for Auditors Pioneer
Recipient of the IIA’s 2007
Bradford Cadmus Memorial
Award.
 Author of “The Auditor’s Guide to
Internet Resources” 2nd Edition
About Jim Kaplan, MSc, CIA, CFE
Richard B. Lanza, CPA, CFE, CGMA
• Over two decades of ACL usage in building automated audit and
cost recovery tools
• Winner of the 2nd Annual ACL User Challenge
• Wrote the ACL publication on how to use the product in 101 ways
(101 ACL Applications)
• Has written and spoken on the use of audit data analytics for over
15 years. Recently was a contributing author of:
• Global Technology Audit Guide (GTAG #13) Fraud in an Automated
World – Institute of Internal Auditors.
• Data Analytics – A Practical Approach - research whitepaper for the
Information System Accountability Control Association.
• Cost Recovery – Turning Your Accounts Payable Department Into a
Profit Center – Wiley and Sons.
• AuditSoftwareVideos.com – Training website devoted to audit
analytic training
• Received the Outstanding Achievement in Business Award by the
Association of Certified Fraud Examiners for developing the
publication Proactively Detecting Fraud Using Computer Audit
Reports as a research project for the IIA
 Please see full bio at www.richlanza.com
About Rich Lanza, CPA, CFE, CGMA
Page 4

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 Gain an appreciation of their success and pitfalls when planning data
analytics.
 Understand some common approaches to overcoming obstacles to
planning data analytics based on case studies from companies and
surveys conducted by the presenters
 See how analytics can maximize the annual audit plan and better
ensure focus is placed on organizational risk.
 Outline an effective data request process to ensure complete and
accurate extractions of data every time.
 Learn how planning analytics can be integrated into top audit areas by
using statistical analytics and scoring approaches.
Learning Objectives
Page 5
IPPF Standard 1210.A3
 Internal auditors must
have sufficient knowledge
of…available technology
based audit techniques
to perform their assigned
work
The Auditor’s Role
Page 6

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Professional Guidance
Page 7
Categories of Audit Software
Automated
Issues
Tracking
Electronic
Work Papers
Risk
Assessment
Continuous
Controls
Monitoring
Anti
Fraud
Governance
Risk
Compliance
Audit
Management
Audit
Resource
Scheduling
Data
Analysis
Page 8

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 Over 550 auditors responded
 More than 70% reported using data analysis software
 85% of those using reported purchasing specifically for data analysis
 68% reported use to improve audit plan sometimes or always
 33% Ad Hoc Beginner (Excel) 37% Intermediate (Excel, ACL, IDEA)
 73% use audit staff for data analysis (no outsourcing)
 44% use ACL, 33% use Access , 25% IDEA
 43% major reason for not using on all audits - staff not trained
 75% said greatest benefit - able to review entire population
 84% performance objectives/compensation not tied to use
 59% indicated would use data analytics if audit programs included
steps
 58% indicated would use if a script library were available or if vendors
provided a lite version of their software
2012 Survey: Using Data Analysis Software
Page 9
Planning Data Analytics
Statistics / Guidance

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 External auditors, internal auditors, fraud examiners, or finance?
 Using ACL in over half your audits?
 What percentage of your company’s data have you mapped?
– 20%
– 50%
– Over 80%
Quick Attendee Survey (Show of Hands)
Page 11
AuditNet – 2012 Data Analysis Software Survey – Why Are You Not Using
D.A.?
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(Company) Size Doesn’t Seem to Matter
For Implementation Rates
Page 13
AuditNet – 2012 Data Analysis
Software Survey
Data Analytics in the Audit Plan
AuditNet Nov. 14, 2012 Webinar (Over 350 attendees)
Page 14

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Planning the Audit Guidance – # 1 and #2
Deep Analytics to Plan Audits – Minimal Guidance
Page 15
Planning the Audit Guidance - Understanding Risks
(AU 314) Mention of Automated Tests
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 http://www.nysscpa.org/trustedprof/107/tp11.htm
Malpractice?
PCAOB – Audit Evidence Standard #15
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Education
Prepares
Organization
Needs-Wants-Pays
Regulation
Requires
Imagination
Transforms
What Drives the Data Auditor?
Page 19
 Use data analytics on almost every audit
– Brainstorm the use data analytics in the audit planning process
– Drop an audit and instead plan 10% for “data fun” across all audits / Understand the
process and benchmark it for future reviews
– Make it part of annual objectives to use the product
– Start looking at recent regulations that are mentioning D.A.s use
 Find cost savings to pay for the usage & Track it & Promote it
– Risk assess the general ledger – stratify by month by account J/E risk scores
– Search for cost recovery opportunities with vendors and improved business methods
– Sell the need for increased software and education
» Also sell the cost/benefit of ACL to other development platforms (especially for prototyping).
Overcoming Obstacles
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 Plan on education and make it routine
– Meet every three weeks on analytics – no matter what
– Build a team of champions to coach the team
– Get everyone else involved…..even if it is with Excel to start
– Make it part of annual objectives to learn the product
 Establish data channels to all (material) parts of the organization
– Have more freedom to extract data as needed
– Obtain quarterly feeds of data
– Obtain data from all locations once a year for audit planning
Overcoming Obstacles
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Effective Data Import Process

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 Asking for data before understanding reporting needs
 Settling for lesser quality data extracts from the company system
 Not knowing what is possible within the tool to import and normalize data
 Not documenting (videotaping) past ways to obtain data
 Not asking for data early enough
 Not obtaining data routinely and building the expectation (UK Bribery Office)
Top Data Import Mistakes
Page 23
AuditNet Nov. 14, 2012 Webinar (Over 350 attendees)
Data Request is Sent Prior…..
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Integrating Analytics into Top
Audit Areas
Where Are You
Using Data Analytics?
Page 26
AuditNet – 2012 Data Analysis
Software Survey

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Types of Analytical Tests (Substantive Test)
Page 27
1. Trend Analysis
2. Ratio Analysis
3. Reasonableness Tests
4. Regression Analysis
“Analytical Procedures – Audit Guide”, AICPA, March 2012
PCAOB – Audit Evidence Standard #15
Other Substantive Tests
Page 28
> Observation
> Inquiry
> Confirmation
> Recalculation
> Re-performance

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Audit Objectives / Controls to Scripts
Page 29
How the Scripts Align to Objectives
Page 30

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Fraud Risk Assessment Sub-Categories
31
Page 32
See the IIA’s website at www.theiia.org
Proactively Detecting Fraud Using Computer
Audit Reports - IIA Research Paper

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When
 Extract journal entries posted on weekends and holidays.
 Extract journal entries relating to the prior year that were made just immediately following a fiscal-year
end.
 Summarize journal entry credits and debits processing by day, month, and year.
Where
 Extract journal entries made to suspense accounts and summarize by the person entering and
corresponding account numbers.
 Extract journal entries to general ledger accounts known to be problems or complex based on past
issues (errors of accounting in journal subsequently corrected by accounting staff or auditors) at the
company or the industry in general.
 Extract debits in revenue and summarize by general ledger account. Summarize journal entries by the
persons entering to determine if they’re authorized.
Specific Tests Based on the 5 Ws
Page 33
Integrating Analytics into The
Audit Plan – Specific ACL
Cases

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Stratification by Month and
Relations Between Years
Page 35
Stratification By Month
Secret Code
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Transactional Scoring
 Modern tests (round numbers, duplicates, missing fields) identify thousands
of ‘suspicious’ transactions, usually about 1 in 5 of all transactions get a
‘red flag’
 Historically at least 0.02 – 0.03 % of all transactions have real problems,
such as a recoverable over-payment
 So roughly 0.00025 / 0.2 = 0.00125 or 1 in 800 ‘red flags’ lead to a real
problem.
Imagine throwing a random dart at 800 balloons hoping to hit the
right one!!!
The Sampling “Problem”
Bottom Line Numbers
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The result is a sampling
methodology that is now based on
Risk as you define it
mathematically in a score
Page 39
Summaries on Various Perspectives
Summarize by
dimensions (and sub
dimension) to pinpoint
within the cube the
crossover between the top
scored location, time, and
place of fraud based on
the combined judgmental
and statistical score
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Combining the Scores ACL Code
(by supplier number below but this could be record number)
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Severity To Value
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GeoMapping Scores – BatchGeo
Page 43
General Ledger Account Analysis
and Unique Journal Entry Test

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Cost Recovery
 A/P and G/L Review Factors
– Accounts that are sole sourced
– Accounts that have too many vendors
– Categories that map to the “recovery list”
– Assess to industry cost category benchmarks
– Top 100 vendors
– Trend analysis over time
– Trend analysis by vendor (scatter graph)
 Purchase Order / Price List
– Match to invoice payments to assess price differences
– Strategic sourcing vendor review
Cost Recovery Opportunity Tests
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 Accounts Payable
 Audit Fee Benchmarking
 Advertising Agency
 Document Fleet
 Freight
 Health Benefits
 Lease
 Media
 Order to Cash
Profit Opportunities Outweigh Analytic Costs
 Proactive Fraud Detection
 Project Fraud
 Real Estate Depreciation
 Sales & Use Tax / VAT / R&D
tax
 Strategic Sourcing
 Telecom
 Travel and Entertainment
 Utilities
Page 47
Integrating Analytics into the
Overall Audit Plan

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 Obtain data at least once a year for use in the planning exercise
– Basic data may all that is needed from key systems and locations
 Run a series of tests across each location’s data
– Consider focusing on general ledger given its broad exposure to the business
– Consider using risk scoring in a consistent fashion across the company
 Prototype a few local audit toolkits each year
– Most cost effective way to develop and ACL is cheaper than almost any other
development platform for finance/audit professionals
– Identify “low hanging fruit” for cost savings and improvements.
Considerations for Overall Audit Planning
Analytic Command Center
Proposed Implementation Visual
Internal Audit’s
Analytic Command Center
Analytics
1. Accounts Payable
2. Accounts Receivable
3. Financial Statement
4. General Ledger
5. Inventory
6. Payroll
7. Revenue
Data Mart
Local Analytic
Toolkit
Feedback from all
locations
Recovery Auditors
Shared Services

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Useful Links
Training | Ideas | Graphics
 www.auditnet.org
 www.auditsoftwarevideos.com
 www.aicpa.org
 www.pcaobus.org

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Connections 2013 change your thinking - integrating analytics into the audit process final