As fraud schemes grow more sophisticated, the methods to combating them must evolve to meet the challenges. The Association of Certified Fraud Examiners recently released the results of a study they conducted on how organizations are using technology as part of their anti-fraud initiatives. The report is based on a survey which polled a wide variety of entity types and industries from across the globe.

How are Organizations Using Data Analysis to Combat Fraud?

Of the 2,255 respondents, 64% are using data analytics for exception reporting and anomaly detection, 54% have set up automated red flag warnings and business rule violation warnings, and 35% are using data visualization for fraud detection. To perform these tests, organizations are using a variety of tools including Excel, ACL, in-house software, Idea, or SAP for the exception reporting and Tableau or Power BI for data visualization.

Which Areas are Being Tested?

As you can see from Figure 1 below, purchasing and disbursements are the most common areas analyzed for potentially fraudulent activity.

Figure 1 - Risk Area

The data used to test for fraud can come from a variety of sources. Nearly 3/4ths of the respondents are using internal structured data (traditional databases) to conduct these analyses, whereas only 30% are using unstructured data such as emails or voicemails. Only 26% are using data from connected devices such as phones. Other sources used include public records (43%), law enforcement (32%), and social media (29%).

What Challenges are Organizations Facing Implementing the Data Analytics?

Organizations reported that the largest hurdle for implementing data analytics was budgetary constraints. This was followed by skill limitations, poor data quality, lack of perceived ROI, legal and regulatory concerns, and excessive false positives from tests performed. With budgetary constraints being the largest obstacle, respondents were asked how they anticipated funding to change in the next two years. About 3/4ths of respondents expected little to no increase, and only 17% expected significant increases.

In Conclusion

The primary goal of this study is to help you understand what anti-fraud technologies your peers are using and to assist you in adopting these technologies in the future. However, the ultimate goal is to help you bolster your fraud prevention techniques and outmaneuver the fraudsters.

If you have any questions on how to get started in adopting anti-fraud technology for fraud prevention, contact a Clark Nuber professional.

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