Planning Data Analytics Into Your Audits – Best

Practices

October 31, 2012

AuditNet and AuditSoftware.Net Collaboration

Brought to you by AuditSoftware.net and AuditNet, working together to providePractical audit software training

Resource links

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Today focused on providing practical data analysis training

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About Jim Kaplan, CIA, CFE

President and Founder of AuditNet®, the global resource for auditors

Auditor, Author, Web Site Guru, Internet for Auditors Pioneer

Recipient of the IIA’s 2007 Bradford Cadmus Memorial Award.

Local Government Auditors Lifetime Member Award

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About AuditNet LLC

• AuditNet® is the global resource for auditors created by Jim Kaplan an Internet for auditors pioneer and recipient of the IIA’s 2007 Bradford Cadmus Memorial Award. The Web site features:

• Over 2,000 Reusable Templates, Audit Programs, Questionnaires, and Control Matrices

• Training without Travel Webinars focusing on fraud, audit software

(ACL, IDEA, Excel), IT audit, and internal audit

• Audit guides, manuals, and books on audit basics and using audit

technology

• LinkedIn Networking Groups

• Monthly Newsletters with Expert Guest Columnists

• Book Reviews

• Surveys on timely topics for internal auditors

Introductions

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Webinar Housekeeping

This webinar and its material are the property of AuditNet® and Cash Recovery Partners. Unauthorized usage or recording of this webinar or any of its material is strictly forbidden. We will be recording the webinar and if you paid the registration fee you will be provided access to that recording within two business days after the webinar. Downloading or otherwise duplicating the webinar recording is expressly prohibited.Please complete the evaluation to help us continuously improve our WebinarsYou must answer the polling questions to qualify for CPE per NASBASubmit questions via the chat box on your screen and we will answer them either during or at the conclusionIf GTW stops working you may need to close and restart. You can always dial in and listen and follow along with the handout

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Richard B. Lanza, CPA, CFE, CGMA

• Over two decades of ACL and Excel software usage• Wrote the first practical 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.• 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

• 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.

Please see full bio at www.richlanza.com

Learning Objectives

Gain an appreciation, based on the attendee participants, of their successes and pitfalls when planning data analytics. Understand some common approaches to overcoming obstacles to planning data analytics based on case studies from companies and survey attendees themselves.Learn how planning analytics can be integrated into top audit areas.Outline an effective data request process to ensure complete and accurate extractions of data every time.See how analytics can maximize the annual audit plan and better ensure focus is placed on organizational risk.

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Technology Standards

IPPF Standard 1210.A3

Internal auditors must have sufficient knowledge of…available technology based audit techniques to perform their assigned work

IIA Guidance – GTAG 13

Internal auditors require appropriate skills and should use available technological tools to help them maintain a successful fraud management program that covers prevention, detection, and investigation. As such, all audit professionals — not just IT audit specialists — are expected to be increasingly proficient in areas such as data analysis and the use of technology to help them meet the demands of the job.

Professional Guidance

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

DataAnalysis

2012 Survey: Using Data Analysis Software

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Over 500 auditors responded as of 11/01/2012 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

Planning Data AnalyticsStatistics From the Audience

AuditNet – 2012 Data Analysis Software Survey – Why Are You Not Using D.A.?

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Today’s Attendees

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Today’s Attendees

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Today’s AttendeesData Analytics in the Audit Plan

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Today’s AttendeesData Analytics in Audit Planning

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Today’s AttendeesData Analytics for Process Flow

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Polling Question #1

What is the top reason why data analytics is not used in the audit?Upper management support

Getting the data

Planning it in to the audit

I don’t know

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Common Approaches to Overcoming Obstacles in Planning With Data Analytics

Planning Data Analytics

Identify the Risk Areas for the Audit Objective

Risks Identified -

Best use of Data Analytics

Planning Data Analytics

Id the Risk Areas - Type of Analysis

Low: Volume / Complexity – Manual Analysis

Medium - High: Volume / Complexity –

Data Analytics Tools

Overcoming Obstacles

Use data analytics on almost every audit Brainstorm the use data analytics in the audit planning process

Risk assess the general ledger – stratify by month by account

Drop an audit and instead plan 10% for “data fun” across all audits

Make it part of “annual objectives”

Use low-cost solutions to start Excel is a great starter tool for small audit shops

Add-ins to Excel can be your next stepping stone and all have 30-day trial licenses

Training can be self study, vendor videos, and webinar based

Work your way up to the more advanced tools from a cost and training perspective

Find cost savings to pay for the usage & Track it

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Integrating Analytics into Top Audit Areas

AuditNet – State of Technology Use -Where Are Data Analytics Used?

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Audit Objectives

1. Purchasing and accounts payable activities are operating effectively and efficiently

2. Expenses are properly authorized, accurate, and complete

3. Receipts are accurate and complete

4. Check processing is safeguarded, authorized, accurate, and complete

5. Audit trails are maintained and timely information is provided to decision makers.

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Audit Objectives to Scripts

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How the Scripts Align to Objectives

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Specific Tests Based on the 5 Ws

Who

Summarize journal entries by the persons entering to determine if they’re authorized.

What

Summarize journal entries by account and repetitive extracts (more than 50 instances) and unique account sequences used in the journal entry (based on the first five debit and credit postings).

Extract nonstandard or manual journal entries (versus a created system such as an accounts payable ledger posting) for further analysis.

Stratify size of journal entries based on amount (using the debit side of the transaction).

Summarize general ledger activity on the amount field (absolute value of debit or credit) to identify the top occurring amounts. Then summarize activity by account and the amount identified for the top 25 appearing amounts.

Scatter-graph general ledger account (debit and credit amounts separately) and numbers of transactions.

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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

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Why

Extract general ledger transaction amounts (debit or credit) that exceed the average amounts for that general ledger account by a specified percentage. (Five times the average is the default.)

Extract journal entries that equate to round multiples of 10,000, 100,000, and 1,000,000.

Extract journal entries with key texts such as “plug” and “net to zero” anywhere in the record.

Extract journal entries that are made below set accounting department approval limits especially multiple entries of amounts below such limits.

Extract journal entries that don’t net to zero (debits less credits).

Specific Tests Based on the 5 Ws

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Mapping Data Elements to Audit Objectives

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Polling Question #2

Which audit objective question below is most easily automated?Does the company have a written code of ethics?

Does the company follow approval limits prior to invoice approval?

Do adequate written procedures exist for invoice processing?

Is check stock safeguarded?

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Effective Data Import Process

Top 10 Data Import Mistakes

1. Not knowing what is possible within the tool to import and normalize data

2. Asking for data before understanding reporting needs

3. Not including knowledgeable system professionals to assist in or review the extract

4. Forgetting to run statistics on amount/date fields5. Not summarizing text code fields (including

invoice numbers to find E+ issues)

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Top 10 Data Import Mistakes

6. Lack of hardcopy information for review in relation to imported data

7. Not validating field totals to batch totals

8. Using report files vs. fixed length system files

9. Getting data in Excel vs. a more raw format

10.Lack of understanding of the various data types

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Quick Process to Running Data

1. Know your audit objectives

2. Align reports to the objectives

3. Use past reports to model /refine reports

4. Set data requirements based on reports

5. Obtain, validate, and normalize data

6. Edit scripts for data needs

7. Run reports and document results

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Data Request Checklist

Actual Files to Obtain File Structure / Record Layout

Indexes to Understand Data

Indexes to Understand Reason Codes

Other non-System Information Needed Loan or Credit Agreement Terms

Data Request Checklist

Computed Fields

• How to use them?

• Where to place them?

Repetitive Audit / Project

vs.

Special Assignments

Data Request Checklist

Data Request Checklist

Outcome

Initial Analysis

Next Steps

Today’s AttendeesData Request is Sent Prior…..

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Clear Data Request

Accounts Payable Data Request.doc

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Polling Question #3

What is NOT one of the top 10 data import mistakes?Asking for data before understanding report

needs

Not validating batch totals to data

Including knowledgeable people in the extract process

Not knowing what is possible in the software

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Integrating Analytics into The Audit Plan

Cost Recovery Opportunity Analysis

Expenses for Analysis

Primarily SG&A

Cost of goods sold (i.e., freight)

Data Files

General Ledger (trial balance)

A/P Invoice Detail Distribution

Purchase Orders

Pricing List

Profit Opportunities Outweigh Analytic Costs

Accounts PayableAudit Fee BenchmarkingAdvertising AgencyDocument FleetFreightHealth BenefitsLeaseMediaOrder to Cash

Proactive Fraud DetectionProject FraudReal Estate DepreciationSales & Use Tax / VAT / R&D taxStrategic SourcingTelecomTravel and EntertainmentUtilities

Cost Recovery Opportunity Tests

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

Stratify Your Data

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=IF(B4>1000,“3. Over $1000",IF(B4>100,“2. Over $100 to $1,000",IF(B4<=100,“1. Up to $100")))

This will create three strata:1. Up to $1002. Over $100 to $1,0003. Over $1,000

Start from highest to lowest – Excel picks the first matching item

The Sampling “Problem” Bottom Line Numbers

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!!!

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Transactional Score

A single score is given to each transaction based on its severity (number of attributes it meets)

Scores are summarized by enterer, vendor, and department (buyer)

Scattergraphs are completed of the results by:

Enterer

Business Partner

Department

…focusing on severity/volume and differences in

these variables

Sampling is completed in each quadrant

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Transactional Scoring

The result is a sampling methodology that is now

based on Risk as you define

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Summaries on Various Perspectives

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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 

Using Vlookup to Combine Scores

Create a record number

Relate sheets based on VLookup

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Severity To Value

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GeoMapping – BatchGeo

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Polling Question #4

What function is mainly used to align all scores in a spreadsheet?MOD()

FIND()

MID()

VLOOKUP()

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Questions?

Any Questions?Don’t be Shy!

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AuditSoftwareVideos.com

Videos accessible for 12-month subscriptions

Repeat video and text instruction as much as you need

Bite-size video format (3 to 10 minutes)

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Professionally produced videos Sample files, scripts, and macros included for ACL™ and Excel™ Instructors with over 20 years experience in ACL™, Excel™ , and more

AuditNet® Survey - 2012 Data Analysis Software Survey

Please help us by taking the survey

Scan the QR Code with your Mobile Device

Or Visit

https://www.surveymonkey.com/s/2012DataAnalysisSoftware

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Thank You!

Jim KaplanAuditNet LLC®1-800-385-1625

Email: webinars@auditnet.orghttp://www.auditnet.org

Richard B. Lanza, CPA, CFECash Recovery Partners, LLC

Phone: 973-729-3944Cell: 201-650-4150Fax: 973-270-2428

Email: rich@richlanza.com

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