SAS: Protecting the Enterprise: Social Network Analysis – Connecting the Dots Fraud Management Institute in partnership with Bridgeforce
Posted: 20 October 2010 | Source: SAS
Few developments in the area of fraud and financial crime1 management (collectively “fraud management”) have created as much excitement, or demonstrated as much potential, as the newly emerging area of social network analysis (SNA). As an emerging technology, SNA offers capabilities that often surpass other analytical solutions in their ability to integrate different pieces of data to form a more complete picture of emerging fraud threats.
Fraud rings are getting bigger and more sophisticated every day. Domestic gangs and organized crime rings have become big players, able to mount attacks whose scale and sophistication dwarfs those of just a few years ago. Crime rings in foreign countries pose an even more serious threat as they launch wide-scale coordinated attacks, possibly with the tacit approval or even the active cooperation of a sovereign state.
To effectively defend against these threats, today’s organizations need to develop the ability to identify them relatively early in their life cycle, so that subsequent activity can be blocked. They also need to develop the ability to learn as much about these threats as possible at any stage of development.
To complicate matters further, organizations need to gather this information from a much wider range of data than they may have considered before. It’s not an exaggeration to say that any channel, of any product line, in any geographic region may contain the keys that are critical to unraveling the secrets of a nascent fraud threat.
Meeting these challenges requires an approach that not only casts a wide net across all possible sources of data, but also is capable of plucking from this net the apparently isolated clues that, when woven together, can create a picture of the overall threat. This is exactly the type of challenge where SNA shines.
Social network analysis is not new. Analysts and investigators have been studying networks for years using spreadsheets and database queries. The emergence of capabilities to construct networks automatically, however, dramatically increases its potential effectiveness.
This white paper discusses both the reasons that many institutions find SNA to be so attractive, and the challenges they face in making the promise of SNA a reality. It is based on interviews conducted with financial institutions ranging from $50 billion to more than $1 trillion in assets, as well as government agencies. There will be a discussion on where organizations want to go, how far they have gotten, and the major challenges they face in making further progress. Also, steps that organizations can take in planning for SNA deployment within their own organization will be outlined.