Using Risk-Based Data Analytics on Comprehensive Datasets 2/28/19

This session will address how you can leverage technology to analyze 100% of your transactional dataset to identify internal control weaknesses and unusual transactions that may pose a higher risk of fraud. The process from data extraction to sample selection to reporting will be covered. As a result of being exposed to examples from various transaction cycles (e.g., procurement, travel, and entertainment, payroll, journal entries) and data analysis technologies (e.g., IDEA, Tableau, Excel), you will be able to envision how and where to implement data analytics in your organization.

Date:
Thursday, February 28, 2019

Time:
Registration begins at 11:30 AM
Lunch begins at Noon
Speaker will directly follow the lunch and session will last until 2:30 pm

CPEs 2

Location:
Shaker Ridge Country Club
802 Albany Shaker Road,
Albany, NY 12211
[Near the Albany Airport]

Speaker:
Kathy Enget Ph.D.,CPA, CFE 

Meal Choices:
Chicken Parmesan, Baked Haddock or Pasta Primavera

Cost:
$20.00 Members of the Albany ACFE Chapter
$30.00 Non-Members of the Albany ACFE Chapter
Registration will be open until 5:00 pm on Tuesday, February 26, 2019.

Click Here to Register Online

Bio:

Kathy Enget, Ph.D., CPA, CFE is an Assistant Professor in the Department of Accounting and Law at the University at Albany – SUNY. Her research and teaching focuses on forensic accounting. Specifically, she concentrates her research on auditing procedures, including nature, timing and extent, particularly as it relates to the detection of fraud, continuous auditing, and continuous monitoring. Prior to entering academia, she had more than 6 years of accounting and auditing experience most recently as a manager at KPMG ForensicTM where she focused on proactive forensic data analytics for primarily internal and external audit clients.

 

Substitution/Cancellation Policy:

Substitutions can be made at any time up until the event but there can be no meal changes, refunds or cancellations after 5:00 pm on February 26, 2019.  No-shows will be individually responsible for full payment.