Acl Data Analytics eBook

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Enabling a Sustainable Data Analytics Program

PEtEr MiLLAr ACL Services Ltd.

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2Enabl ing a Susta inable Data Analyt ics ProgramP E t E r M i l l A r


ContentsWhat can you do to make a difference? ................................................................................ 4

Getting Started! ................................................................................................................... 5

Why you need to establish a data analytics program NOW .................................................... 6

the 6 Steps to a successful data analytics program: ............................................................... 7

Develop Plan.................................................................................................................. 8

Acquire Data .................................................................................................................. 9

Analyze Data ............................................................................................................... 10

review ........................................................................................................................ 11

report ......................................................................................................................... 12

Wrap Up ...................................................................................................................... 13

Summary ............................................................................................................................ 14

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A recent iiA Survey indicated the global recession is having an impact on internal audit activities.

Survey respondents felt that “better risk management could have played a role in preventing the current crisis...internal auditing could have done more to assist their companies in identifying key risks.”

For full details, visit the iiA’s Global Audit information Network at www.theiia.org/GAIN

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When considering the economic crisis and the role you play as an auditor, what can you do to make a difference?

in the iiA report, richard Chambers suggests that audit can help to reduce inefficiencies through CAAts and data analytics. to be successful, audit will need to take the following steps:

Get buy-in from management �

Acquire and reconcile data �

Make it repeatable �

Read on for step-by-step guidelines on how to establish a sustainable data analytics program!

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TIP: Focus on those areas with highest ROI first, they may recover dollars in areas that are a pain point for management

Getting Started!

Obtain Buy-In from Management. Start small and produce high value. Depending on your risk assessment, a great place to start might be with an Accounts Payable analysis. One duplicate payment could pay for the tools needed to implement a cost-recovery program within your organization.

Other reviews you can perform for quick and impactful results are

PCard �

Accounts Payable �

travel & Entertainment Expenses �

Acquiring and Reconciling Data. reconciling your data to make sure it’s complete is key. For example, we like to think there are no fraudulent people in our organization but if the person we’re requesting the data from is the one committing fraud, they might be smart enough to give us everything except the fraudulent data/journal entries. Make sure all the data is there.

Making it Repeatable. Some may not see the long-term value in technology investments. However, the time and efficiency savings you will achieve by making tasks repeatable will save your organization money and will allow your department to keep up with your workload even with limited human resources.

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Why you need to establish a data analytics program NOWidentify trends, correlations or emerging risks that weren’t evident �

Support the need for a business process change �

Garner support needed to push through that business change �

Empower both audit and management �

Cost Savings �

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the 6 Steps to a successful data analytics program:

Develop Plan1)

Acquire Data2)

Analyze Data3)

review 4)

report5)

Wrap-up6)

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Develop Plan

this first step is crucial to identify audits that would benefit from data analysis. Ask yourself these questions:

is this an area of high risk that would benefit from more intensive oversight? �

in prior years, have steps been taken to confirm that complete data populations have been obtained? �

is there a need to focus on particular types of transactions / situations within the larger population? �

Are the audit procedures designed to look for exceptions? �

identify Audit Approach and Schedule

What procedures are required to support the audit objectives? »

Define the specific data analysis tests accordingly »

Define Coverage Desired

Consideration of period cutoff »

Consideration of specific sub-populations (e.g., business units) and / or other specific exclusions »

Define Data and Documentation requirements

What data is required to support the audit objectives? »

Who are the key it contacts associated with the required data? »

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Acquire Datarequest and obtain data �

Develop a standard data request procedure and »data request document

Key Components of the Data request Document »

Overall purpose –

Cutoff requirements –

Specific data elements necessary to support –procedures

Any exclusions required (specific divisions, –locations, etc.)

Acquisition logistics (data file types, media / –transfer methods)

Delivery expectations –

request for control totals and scripts executed –by it

retain documentation within working papers »

Obtain and read in data �

Assess � completeness of data

Compare data received to control totals provided »

reconcile data to source system »

Determine if proper cutoff has been applied »

Assess � quality of data

identify key fields that contain »

Null values –

records or fields that appear incorrect (e.g., –amount fields containing text values, invalid ranges of values, etc.)

records containing fields that exceed a –certain value threshold as determined by the internal audit team

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Analyze DataDevelop and execute analysis logic �

Considerations »

Programming standards = Clarity, Continuity, Quality –

implementation of scripts / programs = reusability, Efficiency –

Order of execution can impact processing time / storage –

Designing to support evidence of procedures performed –

troubleshoot and refine Logic »

review results –

identify and seek areas to improve analysis –

Ensure absence of errors in logic –

refine as required –

Format Output »

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review

Develop / adhere to review procedures

Considerations �

Second level of review – peer review »

technical evaluation of the analysis »

review of analysis to confirm that audit objectives have been met – does this match expectations? »

review of output »

Were results confirmed with the appropriate business / it individuals? »

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reportinterpret results, draw conclusions, prepare report �

Considerations »

Summary Memo – – Outlines the data analysis performed at a high level for the non-technical reviewer.

Procedures Performed – – describes the detailed logic applied in order to execute the data analysis procedures.

Flow Chart – – Documents the program flow when dealing with more complex analysis logic.5

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Wrap Up

retain analytic documentation

Apply data retention standards �

review lessons learned & identify future modifications �6

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14Detect ing and Prevent ing Fraud wi th Data Analyt icsP E t E r M i l l E r


Summary

treat your data analytics implementation as a program because software alone will not get you to where you want to go. A successful program must involve people, processes and technology.

Engage your organization’s people in your program objectives, explaining to them what you are seeking to �achieve and what benefits to the organization will result.

Develop your plan with an understanding that you will need to have recurring access data and have a good �working knowledge of the business processes you want to scrutinize.

recognize that you will need to change not only your audit engagement process, but also how you interact �with the rest of the organization during the course of audits and in subsequent follow-up.

Data analytics technology will help you improve audit efficiency and the overall quality of audit results only if �your staff knows how to use it. training and ongoing development are key elements to a sustainable and effective program.

the benefits are significant - both in terms of the improved confidence in your audit results and the quality of insight you provide. With a sustainable data analytics implementation, you’ll improve your overall audit efficiency and consistency of work performed. these are outcomes definitely worth pursuing.

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