Intelligent Security


Fraud Analytics

Find and Recover Lost Revenues Through Fraud Analytics

Enterprise data warehouses store huge amounts of historical and real-time transactional data that needs to be translated into useful information. Proactive analysis of business data provides an efficient early-warning system for detecting electronic fraud. With information, a company can discover whether losses are due to poor business practices or fraud.

Corporations relying on traditional, reactionary security are left unaware of their losses. Much of today's fraud is an electronic sleight-of-hand used by those familiar with these transactions – sometimes the most experienced employees and most valued customers. Fortunately, the footprint of their fraudulent activity can be captured.

How do you go from data to intelligence? Number crunching alone won't determine behavior or intent. Knowing what to look for and how to find it, will. Illicit behavior is disguised in a business transaction. The right fraud analytics and methods can enable companies to save and recover millions of dollars in lost revenue.
An essential precursor to any investigation, fraud analytics and profile execution reduce the threat of litigation while providing security professionals a consistent discovery method that yields the information they need. It creates a defensible starting point for company and criminal investigations.

Experts in enterprise data warehouse fraud analytics and profile development, Clark Consulting offers a unique approach for reducing abuse:

  • Leverage data to find previously undetectable occurrences
  • Track exposure regardless of the actor – employee or customer
  • Investigate to determine culpability and global cost
  • Use company's existing data
  • Identify trends and characteristics of transactions

Good intelligence information fosters critical decisions which save millions of dollars in lost revenue and unproductive transactions. Put into practice, the process pays for itself in revenues saved and recovered.