Smarter analytics to challenge a new generation of financial criminals
Financial crime is nothing new. Since the dawn of commerce, financial services have struggled against fraud and financial crime. But in today’s rapidly evolving threat landscape, increasingly intelligent financial criminals are using modern digital technologies to take advantage of an attack surface that is broader than it has ever been.
The recent white paper IBM Counter Financial Crimes Management gives some idea of the staggering scale—and costs—of modern fraud and financial crime:
- From 2003 to 2012, emerging markets alone saw $6.6 trillion in illicit financial flows.
Every year, 2 to 5 percent of global GDP is money laundered.
- Organized crime is the origin of 80 percent of cyber crime.
The costs to business that financial crimes incur are not limited to merely the direct effects of such acts. Regulatory costs are now a subject of considerable concern in the financial sector. For example, both the US Treasury Department’s new customer due diligence (CDD) requirements and the European Union’s anti–money laundering (AML) directive allow the fining of both banking institutions and banking executives for non-compliance. And regulatory fines have been on the uptick: In 2014, fines imposed on banks totaled seven times the sum of the fines levied in 2013—and that figure doesn’t even include the increase in fines levied on C-suite executives.
Dealing with smart financial criminals through smart analytics
In today’s wired economy, virtually all banking is conducted electronically. Accordingly, fewer and fewer financial institutions now have direct personal relationships with their customers, and modern financial criminals have exploited this trend. To successfully fight fraud and money laundering, financial institutions need analytic insight into who their customers are, as well as into how customers are connected to each other, if they are to evaluate the legitimacy of financial transactions.
- Identity resolution: Who is whom?
By accumulating identity context over time, entity analytics uses various enterprise sources of information to determine whether individuals really are who they claim to be.
- Relationship resolution: Who knows whom?
Accurate identities can help uncover complex relationships by allowing the processing of resolved identity data to determine whether people are—or have ever been—related.
- Multi-layered analysis: Who does what?
With customer identities and relationships well established, additional layers of analytics processing can help financial institutions evaluate all transactions and non-transactional behavior of an entity—and, optionally, of associated entities—to assess downstream compliance and fraud risks.
Putting the pieces together with context computing
These insights are not only complemented, but enhanced, by further insights attained through a new generation of context computing technology. This technology—an integral part of the next-generation IBM Counter Financial Crimes Management platform—helps banks build a better understanding of the three aforementioned areas over time by treating individual data points as if they were jigsaw puzzle pieces. By looking for relationships between pieces, entity analytics can take a large data set and begin identifying pieces that may be related—and then help determine how they are connected.