Fraud Magazine recently published a good article on using data analysis for fraud detection. One of the notable aspects is that the frauds described do not require particularly complex analysis to discover. Some fairly basic tests can provide indicators of the most commonly performed types of fraud.
Implementation of a suite of tests designed to identify a range of different types of fraud can certainly be a very effective part of any anti-fraud program. An additional benefit can also arise if it becomes known within the organization that a proactive fraud detection system is in place, particularly if no one knows exactly what tests are being performed. Potential fraudsters may well think twice if they know that someone is keeping an automated eye on things…
Here’s an excerpt from the article:
BEST PRACTICES
Design a data analytics process that clearly identifies and fully explains:
- What organizational data to collect.
- When and how to obtain the organizational data.
- How to integrate the process into the organization’s fraud risk assessment program.
- What tools and techniques to use for evaluating the potential existence of fraud.
- How to evaluate the process’s effectiveness in detecting and preventing fraud.
- How to report findings and recommendations.
- Standards for tracking the timeliness and effectiveness of remedial actions.
To read the article Devil in the details: anti-fraud data analytics, click here.
And what about you – what analytic tests are you using to find fraud?
