USING DATA ANALYTICS TO DETECT AND PREVENT FRAUDULENT ACTIVITY
RC: In your experience, what role can data analytics play in detecting and preventing fraudulent business activities? To what extent can sound data analytics compensate for weaknesses in internal controls?
Padilla: Data analytics can be a powerful component in your overall corporate compliance effort—it doesn’t compensate for weakness in internal controls, but rather enhances existing controls. Data analytics provides an alternative approach to detecting fraud, one that doesn’t rely on the same methods as existing controls and that often can detect issues those methods miss. In addition to strengthening your overall corporate compliance program, this also sends a strong deterrent message to employees, vendors, agents or other entities of interest that might be considering perpetrating improper activities.
RC: What advice would you give to companies in terms of designing and implementing an effective anti-fraud program that incorporates data analytics and related software? What are the key considerations and techniques that should be considered?
Obuchowski: When designing and implementing a data analytics effort, you need to start with the team, not the tools, and the team will start with the data. You need a team with the experience to understand what data patterns should look like in your organisation. They need to understand your systems and control environment, to understand the data inputs and outputs to ensure that they are working with the right data to begin with. You have to look at your data governance practices to make sure your data is accurate, verifiable and reliable. With the right team in place and the right data to work with, the tools will be relatively easy to put in place.
Jul-Sep 2015 Issue