Fraud is Happening at Your Organization; You Just Don’t Know It

The ACFE Anti-Fraud Playbook declares that fraud is happening at your organization; you just don’t know it, and then it provides ten “plays” drawn from best practices and leading guidance designed to help reduce fraud risk. One play provided as a best practice is the use of data analytics to uncover fraud. 

The playbook asserts that data analytics is a powerful fraud prevention, detection and investigation tool, making it an important part of an effective and holistic fraud risk management program.

As part of utilizing data analytics in preventing and detecting fraud, you must understand and organize all relevant data. Preparing the data for analysis includes data extraction and consolidation and data cleansing. 

Data extraction and consolidation is collecting the relevant data, selecting necessary records and variables and integrating or merging records from multiple data sources. One challenge of working with multiple data sources can be that some of the data may be organized and formatted (structured) and some of the data may be qualitative in its native format (unstructured).  

Data cleansing should be employed: removing unwanted observations, fixing structural errors, handling missing data and managing unwanted outliers.

Preparing the data for analysis can be time-consuming. However, it is a valuable investment that is necessary at the beginning of a data analytics project in ensuring that data is ready for analysis. ETL (extract, transform, load) software such as IDEA or Alteryx is designed to assist in the data preparation phase.

The next step in evaluating potential fraud is then the actual analysis of the data itself. This can be done by utilizing statistical tools such as Alteryx, Excel, or Power BI. After the data is analyzed, data visualization software such as Tableau or Power BI can be used to understand and communicate the data.

It can be very challenging to know how to pull all of the disparate pieces of data together into a cohesive final analysis product that is useful in preventing and detecting fraud. Schneider Downs’ professionals have years of experience using the software listed above in data analytics projects and have helped many organizations prevent, detect or investigate fraud. 

If you have questions or concerns about fraud risk, or would like to discuss the use of data analytics as a way to evaluate potential fraud, please contact Tom Pratt or Brian Webster.


You’ve heard our thoughts… We’d like to hear yours

The Schneider Downs Our Thoughts On blog exists to create a dialogue on issues that are important to organizations and individuals. While we enjoy sharing our ideas and insights, we’re especially interested in what you may have to say. If you have a question or a comment about this article – or any article from the Our Thoughts On blog – we hope you’ll share it with us. After all, a dialogue is an exchange of ideas, and we’d like to hear from you. Email us at [email protected].

Material discussed is meant for informational purposes only, and it is not to be construed as investment, tax, or legal advice. Please note that individual situations can vary. Therefore, this information should be relied upon when coordinated with individual professional advice.

© 2022 Schneider Downs. All rights-reserved. All content on this site is property of Schneider Downs unless otherwise noted and should not be used without written permission.

our thoughts on
Zero-Based Budgeting: The Continued Pursuit of Savings
Post-Pandemic Fraud Landscape
Has the Pandemic Increased the Value of Golf Courses?
How To Identify Supply Chain Vulnerabilities
Private Equity Activity Update
Register to receive our weekly newsletter with our most recent columns and insights.
Have a question? Ask us!

We’d love to hear from you. Drop us a note, and we’ll respond to you as quickly as possible.

Ask us
contact us

This site uses cookies to ensure that we give you the best user experience. Cookies assist in navigation, analyzing traffic and in our marketing efforts as described in our Privacy Policy.