Real-time Detection of Fraudulent Activity
According to the Association of Certified Fraud Examiners, fraud costs organizations trillions of dollars worldwide and impacts most industries. Use Splunk to detect and prevent fraud in real-time to avoid fraud-related costs and protect your customers and partners from the results of fraud.
How Can Splunk Detect Fraud?
Simply put, the patterns of fraud are often found in an organization's machine data or log files, just as the patterns of an advanced cybersecurity threat are often revealed in machine data. Authentication systems, firewalls, databases, billing systems and other systems all generate machine data, which likely contain the subtle patterns of fraud when and where fraud exists.
By indexing relevant machine data in Splunk, and then writing the appropriate searches and correlations to identify the patterns of fraud, an organization can detect and alert on fraud in real time and act to prevent it before it adversely impacts the bottom line.
Additionally, Splunk can create baselines of normal activity and then apply statistics and math to the baselines to identify statistical outliers and anomalies that might be fraud. This can help anti-fraud teams creatively identify new patterns of fraud previously unknown to them. Lastly, organizations can use the flexible reporting in Splunk to visualize and measure fraud any way they see fit.
What do the Patterns of Fraud Look Like?
These patterns vary, just as the behaviors of a cybercriminal vary. This means there is no magical "silver bullet" search to detect fraud, and the methods to do this will vary for each organization and each industry. The flexibility of Splunk software lets anti-fraud teams at any organization create the searches specific to their organization to detect fraud.
Here are a few examples of fraud across completely different industries, and what their related fraud patterns might look like. Users can easily turn each of these patterns into real-time searches using Splunk and generate alerts if search parameters are met.