Exploring Data Analytics & CAATsSource: Caseware IDEA pot

Auditing ERP Applications – Case Study Audit of Staff Claims • Medical Claims • Transport Claims Why audit ERP applications using data analytics?. “RECEIPT NO.” , “STAFF ID” and “CLINIC

Exploring Data Analytics & CAATs

Source: Caseware IDEA

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Auditing ERP Applications – Case Study

Audit of Staff Claims

• Medical Claims

• Transport Claims

Why audit ERP applications using data analytics?

• Data analysis approach allows detection of non-compliances and help organisation achieve value-for-money

• Review ALL (100%) of transactions vs sample 30 claims

How to approach audit of ERP applications

• Step 1: Import data from ERP system i.e Excel or flat files

• Step 2: Define field definition (text, numeric, date)

• Step 3: Run analysis i.e exceptions, duplicates, patterns

• Step 4: Report exceptions, anomalies, patterns

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Auditing ERP Applications – Case Study

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Use of IDEA in Audit of Staff Claims (Medical)

Obtain list of staff medical claims from ERP system for period of interest ( e.g all transactions for 1 year)

Identify key fields for testing i.e “RECEIPT NO.” , “STAFF ID” and “CLINIC/HOSPITAL”

Summarise by “STAFF ID”, followed by

“RECEIPT NO.” and analyse for anomalies

Run duplicates test on “RECEIPT NO.”

Detecting Duplicate Claims

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Use of IDEA in Audit of Staff Claims (Medical)

Obtain data, identify fields of interest i.e “RECEIPT NO.”,

“RECEIPT DATE”, “STAFF ID”

Run duplicates test on

“RECEIPT NO.” and “RECEIPT DATE”

Query HR on duplicate payment

Detecting Duplicate Claims

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Use of IDEA in Audit of Staff Claims (Transport)

Audit Observation #1

Non-deduction of Normal Travel Expenses from Office to Home for journeys Starting or Ending from Home

1

• Obtain staff travel claims data for 1 year

• Identify fields of interest i.e “FROM”, “FROM_TO_HOME”,

“OFF_DAY”, “STAFF ID”

2

• Extract FROM = “Home”, FROM_TO_HOME = “N” and OFF_DAY = “N”

• Do similar for TO = “Home” etc

3

• Flags out all transactions where staff did not deduct the cost

of journeys starting or ending at “home” since reimbursement policy does not allow claims for journeys made from home to workplace

Detecting Erroneous Claims

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Use of IDEA in Audit of Staff Claims (Transport)

Audit Observation #2

Possible Duplicate Taxi Claims and Claims without Valid Taxi Receipt Numbers

1

• Obtain staff travel claims data for 1 year

• Identify fields of interest i.e “RECEIPT_NO”

2

• Extract data where “RECEIPT_NO” is not “” and test for duplicates

• Extract data where “RECEIPT_NO” is “” (blank)

3

• Flag out all exceptions to business rules and query department responsible for anomalies

Detecting Erroneous Claims

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Use of IDEA in Audit of Staff Claims (Transport)

Audit Observation #3

Unusual multiple journeys within the same day by same staff

1

• Obtain staff travel claims data for 1 year

• Identify fields of interest i.e “RECEIPT DATE”, “STAFF ID”

2

• Summarise by “RECEIPT DATE” and “STAFF ID”

• Sort by “NO_OF_RECS” (no of records)

3

• High “NO_OF_RECS” indicate multiple journeys made on same day by same staff Unusual unless staff is doing delivery

Detecting Erroneous Claims

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Use of IDEA in Audit of Staff Claims

• Walkthrough and document business process

• Identify key controls for testing

Understand

business process

• Identify and understand data available

• Key fields for testing

Obtain data of

interest

• Do field statistics or summarise all fields to get overall picture of data

Get big picture

• Run analysis for exceptions to business rules

Analyse for

exceptions

Using a Data Driven in Auditing ERP

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Understanding the Risks of

Hosting ERP Data with

Cloud Computing

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Connecting with Cloud

Cloud Computing is already here:

• Cloud computing is the delivery of computing as a service rather than

a product, whereby shared resources, software and information are provided to computers and other devices as a utility (like the electricity grid) over a

network (typically the Internet)

Wikipedia (http://en.wikipedia.org/wiki/Cloud_computing)

• Cloud computing in consumer space is pervasive

• Email services: e.g Google Gmail, Microsoft Hotmail

• Instant messenging: e.g Yahoo Messenger, Microsoft Live, Gmail Gtalk

• Web content management: e.g blogger, wordpress

• Cloud computing in business space is growing

• Refer to OpenCloud Taxonomy

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