Today’s organizations generate and manage tremendous amounts of data, from transaction logs and demographic information to social media activity and online traffic data. In addition to this information, companies with strong business intelligence capabilities extend beyond internally collected data, utilizing third-party databases to gain deeper analysis and insights.
The increasing number of affordable and powerful tools allows companies to develop extensive analytics platforms that extend beyond sales and into other key areas of the business. In fact, data analytics should be a critical weapon in every organization’s fraud protection strategy to guard against loss and reduce vulnerability to regulatory enforcement.
Statistical sampling is typically utilized during internal audit procedures or in response to a suspicion of fraud, but that inherently only focuses on a portion of the data, and leaves vast amounts of unanalyzed information. Conversely, data analytics utilizes forensic techniques to analyze the entirety of the population of data, looking for unusual characteristics that might indicate fraud, enabling high-risk transactions to be flagged for further examination.
By leveraging data analytics, companies can identify potential fraud, waste, and abuse and develop proactive steps to minimize the risk of future misconduct. Read our white paper to understand more about the capabilities of data analytics, and three techniques that organizations can use to bolster anti-fraud programs:
