Enhanced Fraud Detection with Data Analytics

Fraud Detection

Controls that are designed to mitigate the risk of fraud are not perfect. Enterprise software such as Oracle and SAP may have built-in controls, but they are limited in scope to the data and processes that the software "touches". The most successful fraudsters know how to exploit interfaces between different processes and systems. Furthermore, the typical fraud case persists for 14 months prior to detection*.

Deploying data analytics for continuous testing can overcome many of the limitations of traditional fraud detection. Timely and appropriate detection will help organizations mitigate the impact of frauds. Robust fraud detection systems will also act as powerful deterrents.

In this session we will raise awareness about the various types of frauds and how they can be detected using automated data analysis techniques.

We will also take a look at the *ACFE Report to the Nations - 2020 Global Study on Occupational Fraud and Abuse