Course Detail()

UTAP Funding

7.00 CPE Hours (Category 1, Category 2, Category 3, Category 4, Others)
Classroom

As this class places strong emphasis on the hands-on experience, you will be working with data for the majority of the time in the class. To optimize the learning experience, it is mandatory for all participants to be equipped with a Window laptop, pre-installed with Microsoft Excel 2010, 2013, 2016 (full licence) or any latest version.

There has been an explosive growth of data over this decade. The advent of “Big Data” has accentuated the challenge of fraud detection.

The traditional approach of sampling check is considered not as effective in view of the huge amount of transaction data.

Forensic analytics leverage on data analysis technique to search the complete database for exceptions to pre-determined rules. These exceptions are further scrutinized and narrowed to a smaller list for investigation for possible fraud and errors.

This course introduces application of forensic analytics to detect fraud and errors in payment transactions:

  • Explain how data mining and forensic accounting a powerful tool in forensic data analytics.
  • Identify ways to perform fraud risk assessment with fraud scenario.
  • Describe how to Integrate fraud test approach procedure within the internal control approach.
  • Apply the exceptions to specified business rules with a fraud risk statement approach.
  • Demonstrate the fraud test approach into forensic data analytics.

Programme Outline

 
  • Explain the two key components of forensic data analytics
  • Recognize the limitations of traditional audit approach of sampling for fraud detection in Big Data environment
  • Explain the processes and pre-requisites in forensic data analytics
  • Apply fraud risk statement and business rules to identify exceptions to flag breaches of internal control, errors, and potential fraud.
  • Apply forensic data analytics to high-profile fraud cases.


Participants are advised to have basic knowledge of Excel spreadsheet application.

 

Training Methodology
Face to face classroom session, power point presentation materials, group discussion, hands on exercise, polls and video clips.

 

Closing Date for Registration
1 week before programme or until full enrolment.

Intended For

  • Finance professionals in business
  • Internal auditors
  • External auditors

Schedule & Fees

Testimonial

Funding

1] NTUC Union Training Assistance Programme (UTAP)
UTAP (Union Training Assistance Programme) is an individual skills upgrading account for NTUC members.

To find out more on the UTAP funding and support validity period please click here.

Should you have queries on the funding scheme, you can email to UTAP@e2i.com.sg or call NTUC Membership Hotline at 6213-8008

Programme Facilitator(s)

As this class places strong emphasis on the hands-on experience, you will be working with data for the majority of the time in the class. To optimize the learning experience, it is mandatory for all participants to be equipped with a Window laptop, pre-installed with Microsoft Excel 2010, 2013, 2016 (full licence) or any latest version.

There has been an explosive growth of data over this decade. The advent of “Big Data” has accentuated the challenge of fraud detection.

The traditional approach of sampling check is considered not as effective in view of the huge amount of transaction data.

Forensic analytics leverage on data analysis technique to search the complete database for exceptions to pre-determined rules. These exceptions are further scrutinized and narrowed to a smaller list for investigation for possible fraud and errors.

This course introduces application of forensic analytics to detect fraud and errors in payment transactions:

  • Explain how data mining and forensic accounting a powerful tool in forensic data analytics.
  • Identify ways to perform fraud risk assessment with fraud scenario.
  • Describe how to Integrate fraud test approach procedure within the internal control approach.
  • Apply the exceptions to specified business rules with a fraud risk statement approach.
  • Demonstrate the fraud test approach into forensic data analytics.

Programme Outline

 
  • Explain the two key components of forensic data analytics
  • Recognize the limitations of traditional audit approach of sampling for fraud detection in Big Data environment
  • Explain the processes and pre-requisites in forensic data analytics
  • Apply fraud risk statement and business rules to identify exceptions to flag breaches of internal control, errors, and potential fraud.
  • Apply forensic data analytics to high-profile fraud cases.


Participants are advised to have basic knowledge of Excel spreadsheet application.

 

Training Methodology
Face to face classroom session, power point presentation materials, group discussion, hands on exercise, polls and video clips.

 

Closing Date for Registration
1 week before programme or until full enrolment.

Intended For

  • Finance professionals in business
  • Internal auditors
  • External auditors

Programme Facilitator(s)


No course instances or course instance sessions available.