ACL ESSENTIALS€¦ · Identifies payroll adjustments made after the payroll cut off date. ANALYTIC...

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SALARIES & PAYROLL ACL ESSENTIALS Get insight into your ERP process health, compliance & financial exposure

Transcript of ACL ESSENTIALS€¦ · Identifies payroll adjustments made after the payroll cut off date. ANALYTIC...

Page 1: ACL ESSENTIALS€¦ · Identifies payroll adjustments made after the payroll cut off date. ANALYTIC LOGIC Extracts changes made after payroll cut off to show users what changes have

SALARIES & PAYROLL

ACL ESSENTIALSGet insight into your ERP process health,

compliance & financial exposure

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Page Analytic Name

Employee names on the payroll that match a vendorPR Analytic 01

Ex-employees paid more than 60 days after termination datePR Analytic 02

Payroll payments made to inactive employeesPR Analytic 03

Payroll payments to employees before their start datePR Analytic 04

Analysis of new hiresPR Analytic 05

Multiple annual bonus payments in one yearPR Analytic 06

Payroll adjustments made after the payroll cut off datePR Analytic 07

Payroll payments where the bank accounts are the samePR Analytic 08

Payroll payments where Social Security Numbers (SSN) are the samePR Analytic 09

Excessive overtime hours workedPR Analytic 10

Multiple payroll payments to the same bank account within 30 daysPR Analytic 11

Version 6.0.0 –2018/02

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Identifies employee names on the payroll that match a vendor on the vendor master file

ACCOUNTS PAYABLE

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ACL ESSENTIALS | SALARIES & PAYROLL | PR_ANALYTIC_01_PRCS101

CONTEXTInstances where the employee and vendor names agree should be investigated as these could possibly indicate fraudulent transactions and/or incorrect employee/payroll master data.

RISKPossible fictitious/incorrect employees created, resulting in fraudulent/incorrectpayroll payments.

PROCEDUREIdentifies employee names on the payroll that match a vendor on the vendormaster file.Note: Reimbursed employee vendors could appear in the results as falsepositives.

ANALYTIC LOGICExtracts for the selected month’s payroll data and compares the first and lastnames to the names of vendors on the master file.

OUTPUT RESULTS FIELD NAMES

Employee Number ID Number First Name Last Name Vendor Name Vendor Number

OUTPUT VISUALIZATION EXAMPLES

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Pay Date Net Payment

Total exceptions by

vendor

Total exceptions by

employee number

and vendor

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Identifies where ex-employees were paid more than 60 days after termination date

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CONTEXTSalary payments typically end promptly after the employee termination date. Any payments made to an ex-employee after the termination date could indicate incorrect and/or fraudulent payments, and should be investigated.

RISKIncorrect and/or fraudulent payroll payments.

PROCEDUREIdentifies where ex-employees were paid more than 60 days after theirtermination date .

ANALYTIC LOGICExtracts for the selected month’s payroll data and HR master data, analysing fortransactions in payroll occurring greater than 60 days after the termination dateof the ex-employee found in the HR master data.

OUTPUT RESULTS FIELDS

OUTPUT VISUALIZATION EXAMPLES

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Personnel Area Code Personnel Area First Name Last Name Employee Status

Employee Number Pay Date Termination Date Net Payment

Termination date

by net Payment

Net amount by

termination date

Start Date

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Payroll payments made to inactive employees

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RISKIncorrect and/or fraudulent payroll payments.

PROCEDUREIdentifies payroll payments made to inactive employees.

ANALYTIC LOGICExtracts for the selected month’s payroll data and HR master data, analysing fortransactions in payroll occurring where the employee record in the HR masterdata indicates the employee is inactive.

OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

CONTEXTPayments to inactive employees should be investigated to determine the validity of the payment.

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Personnel Area Code Personnel Area First Name Last Name Employee Status

Start Date Termination Date Net Payment Pay Date

Pie chart of

exceptions by

Employee Number

Exceptions by

Employee Status and

Personnel Area

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Identifies payroll payments to employees before their start date

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RISKIncorrect and/or fraudulent payroll payments, namely paying an employee priorto them commencing employment.

PROCEDUREIdentifies payroll payments to employees before their start date.

ANALYTIC LOGICExtracts the start dates of new hires and compares to the current payroll date inthe current month payroll file.

CONTEXTIt is not expected that any employee benefits from a payroll transaction prior to their employment commencement date.Identified instances should be investigated to determine the reason for the payment as well as verifying the review and approval of the payment.

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OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

Personnel Area Code Personnel Area First Name Last Name Employee Status Start Date

Net PaymentPay Date

Net payment

by start date

Heat map of total

net payment

exceptions

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Extracts new hires whose start date is after the payroll pay date

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RISKLate/untimely payroll payments.

PROCEDUREIdentifies new hires who are employed in a particular payroll month that havebeen paid in that same month.

ANALYTIC LOGICExtracts new hires from the current month payroll and if their start date in theHR data is after the payroll date, this is flagged as a new hire.

CONTEXTThe accuracy of critical employment information captured for new hires, such as employment start date, should be verified to ensure new hires are paid in a timely manner. This will also allow an organisation to identify potential ghost employees entered into the system.

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OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

Personnel Area Code Personnel Area First Name Last Name Employee Status Start Date

Net PaymentPay Date

Bubble chart of net

payment

exceptions

Net payment by

start date by

Personnel area

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Identifies annual bonus payments made more than once to an employee up to one

year back

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RISKIncorrect and/or fraudulent payroll payments.

PROCEDUREIdentifies annual bonus payments made more than once to an employee up toone year back.Note: During scoping, annual bonuses are specifically identified to ensureincentives or other non-annual bonuses are not treated as annual for thisanalytic.

ANALYTIC LOGICExtracts a rolling twelve month annual bonus payments table and identifies thosethat were paid more than once in this period.

CONTEXTAnnual bonus means once a year. When multiple bonus payments are made to the same employee it raises a concern regarding the accuracy and validity of these bonus payments and should be investigated.

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OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

Employee Number First Name Last Name Pay Date Bonus Amount Bonus Description

ID Number

Bonus amount by

pay date and bonus

type

Bonus amount by

employee number

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Identifies payroll adjustments made after the payroll cut off date

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RISKIncorrect and/or unauthorised payroll adjustments.

PROCEDUREIdentifies payroll adjustments made after the payroll cut off date.

ANALYTIC LOGICExtracts changes made after payroll cut off to show users what changes havebeen made. These can be further investigated by payroll or audit to understandthe nature of such late changes.

VARIABLESThe payroll cut off date is determined during scoping in Quick.

OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

CONTEXTPayroll adjustments after cut-off date should be investigated to confirm accuracy and validity of these changes.

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Employee Number TR Class ITYPE Change Date

Number of Changes

User Name

Employee Status Termination Date

Number of changes

by date changed

Employee Number by

number of changes

User ID

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Identifies payroll payments where the bank accounts are the same

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RISKIncorrect and/or fraudulent payroll payments.

PROCEDUREIdentifies payroll payments where the bank accounts are the same.Note: Married couples with joint bank accounts are false positive exceptions.

ANALYTIC LOGICExtracts the combined fields of bank account number and bank branch code towhich payroll payments have been made and performs a duplicate check.

CONTEXTPayments to similar bank accounts should be investigated to ensure the accuracy and validity of these payments.

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OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

Personnel Area Code Personnel Area Employee Status Employee Number First Name Last Name

Bank Account Number ID Number Start Date Termination Date Pay Date Net Payment

Pie chart of net

payment by bank

account numbers

Heat map of total net payment exceptions by bank account number and employee

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Identifies payroll payments where employee national identification numbers are the same

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RISKPossible fictitious/incorrect employees created, resulting in fraudulent/incorrectpayroll payments.

PROCEDUREIdentifies payroll payments where employee social security numbers are thesame.

ANALYTIC LOGICExtracts all duplicates on the social security number field in the selected month’spayroll.

CONTEXTDuplicate social security numbers could be because of incorrect employee master data or because of fictitiously created employees. These instances should be investigated.

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OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

Personnel Area Code Personnel Area Employee Status Employee Number First Name Last Name

ID Number Termination Date Pay Date Net Payment

Total net payment

exceptions by

employee number

Total net payment

exceptions by

employee number

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Identifies where overtime hours worked exceeds a configurable threshold

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RISKIncorrect and/or fraudulent payroll payments.

PROCEDUREIdentifies where overtime hours worked exceeds a configurable threshold.Note: If local legislation prescribes a maximum number of hours employees canwork in a month, this analytic can assist with complying to these requirements.

ANALYTIC LOGICExtracts overtime hours in excess of a configurable threshold for furtheranalysis.

CONTEXTOvertime claims should be properly reviewed and approved to confirm accuracy and validity. Overtime payments exceeding the norm/expected levels should be investigated to ensure it is valid and accurate.

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OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

Employee Number First Name Last Name ID Number Total Overtime

Overtime 1 Quantity Overtime 1.5 Quantity Net PaymentOvertime 2 Quantity

Total Overtime by

employee number

Total net

payment by

overtime and

employee

Total overtime

by employee

number

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Identifies multiple payroll payments to the same bank account within 30 days

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RISKIncorrect and/or fraudulent payroll payments.

PROCEDUREIdentifies multiple payroll payments to the same bank account within 30 days.

ANALYTIC LOGICExtracts payments in the last 30 days and identifies where more than onepayment was made to the same bank account. Based on the assumption that anemployee gets paid once a month, exceptions for this analytic present a potentialissue for further investigation.

CONTEXTMultiple payments within a specific period raises a concern as payroll payments typically are executed once a month. These payments may be incorrect and/or fraudulent and should be investigated.

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OUTPUT RESULTS FIELD NAMES

OUTPUT VISUALIZATION EXAMPLES

Personnel Area Code Personnel Area Employee Status Employee Number First Name Last Name

Pay Date Bank Account Number Net Payment Total Deductions Total Earnings

Hashed Identification Number Start Date Termination Date

Exceptions by bank

account number

and employee

number

Total net payment

exceptions by bank

account number