Using IDEA to Keep Payroll Fraud in Check

May 24, 2016

I’m at the IDEA User Conference this week and what an opportunity to mingle with IDEA power users and enthusiasts! My first session was led by Audimation Services’ Jill Davies and Carol Ursell on how to use IDEA to detect payroll fraud.

According to the most recent version of the Report to the Nations from the Association of Certified Fraud Examiners (ACFE), payroll fraud was reported in 8.5% of nearly 2,500 cases and had a median loss of $90,000. This sizeable loss made it worthwhile for participants of this hands-on session to learn more about leveraging IDEA Data Analysis software to unearth fraud schemes.

Within payroll, fraud can occur in many ways, including through:

  • Ghost employees (fictitious, terminated, pre-employment employees)
  • Real employees being paid twice
  • Employees being paid after termination
  • No-show employees
  • Disguised compensation (i.e., salary adjustments)
  • Overtime fraud (overstatement of hours worked for fraud or compensation adjustment)
  • False adjustments and reimbursements
  • Unauthorized changes (temporary and permanent)

After detailed discussions on how to build the fraud scenario and understanding the fraud audit approach, Davies and Ursell focused on using IDEA for data mining. This included combining HR and payroll transaction data to detect scenarios that may indicate fraud, such as:

  • Unusual net pay
  • Missing bank information
  • Duplicate tax identification numbers
  • Different employees with the same bank information
  • Employees over retirement age
  • Employees without benefits deductions
  • When manual checks are issued
  • Employees with no paid time off
  • Terminated employees
  • Employees paid after termination
  • Employees with deposit-type changes
  • Paid employees not on HR master

The session provided an opportunity for attendees to not only learn about payroll-specific scenarios but to also ask questions on performing particular functions or optimizing their analysis process. Given the number of nodding heads and discussions, this session proved to be a valuable resource for all participants.

Not at the 2016 IDEA User Conference but would like to know more training on how to use IDEA Data Analysis software for detecting fraud? Visit Audimation Services’ Training & Events page to view upcoming courses in the United States or request specific training for your organization. You can also visit the CaseWare Analytics Training page for training opportunities outside of the US.

Looking for a payroll monitoring solution that detects erroneous and fraudulent activities before payments are made? Read about the CaseWare™ Analytics Payroll Monitoring solution.

 

About Anu Sood:

Anu Sood is the Director of Product and Corporate Marketing at CaseWare Analytics and is responsible for the company’s global marketing strategy. Prior to CaseWare Analytics, Anu worked in various roles in the high-tech industry and her accomplishments range from writing software for telephone switches to launching a new global satellite communication service. Anu has extensive experience in strategic marketing, corporate communications, demand generation, content marketing, product management, product marketing and technology development. 

Connect:  Anu Sood

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