Layer 5 Big Data Analytics for Fraud and Security will subsume Layer 4 Enterprise Fraud Management projects

I had two calls today with Gartner clients about enterprise fraud management, which is all about managing and preventing fraud or misuse across products and channels. I look at fraud prevention and management through the lens of a five layered approach (See Gartner Research Note “The Five Layers of Fraud Prevention”), and enterprise fraud management can be accomplished through Layers 4 or 5.

Layer 4 technology correlates fraud scoring for transactions across product lines and channels as they occur. It is implemented ‘inline’ to the transaction streams and as such requires a lot of system and data integration throughout the life of the changing applications.

Layer 5 enables big data analytics using different techniques such as entity link analysis, social network analysis, temporal or geospatial analysis and more. It basically integrates structured and unstructured data offline (outside the transaction streams) and therefore does not require modification to source systems. Layer 5 can generally be implemented much faster than Layer 4, especially in big enterprises with lots of legacy applications.

Enterprise users value speed and ease of implementation, along with flexibility and scalability. Layer 5 gets them there faster than Layer 4 when it comes to managing fraud across the enterprise. Of course, like everything else it’s no panacea. We outline the risks and pitfalls in our research note “Use Big Data Analytics to Solve Fraud and Security Problems.”

Enterprises will still need to implement Layers 1, 2 and 3 to protect users and accounts from intrusive and criminal activities as they occur.

But when it comes to looking across enterprise activities, Layer 5 will prevail over Layer 4 because of faster times to results, implementation ease and application flexibility. Both Layers 4 and 5 are complementary but we advise users to start with Layer 5 for the reasons stated above.