“Big data” is a much used, little understood technology term that software vendors say can improve profitability and lower costs in fields as distinct as healthcare and fashion. In financial crime, big data is touted as a key to enhanced compliance, improved monitoring and streamlined reporting. Does big data have practical value or is it all just hype?
The term “big data” refers to massive amounts of data collected over time and that are difficult to analyze by use of common database management tools. Big data may include transactions, activity logs, data about accounts, customers and entities from internal and external sources, surveillance photos and videos, and unstructured text from emails, blogs and other social media sources.
As the cost of storing data has decreased significantly, financial institutions, companies and government agencies, are storing more and more data. This includes the US National Security Agency, which recently was the focus of unwanted headlines for its Prism program by which it acquired mountains of data of telephone calls made by millions of people worldwide. With a collection of vast data comes the challenge of accessing it, making sense of it and leveraging it for strategic and tactical purposes.
Many financial crime specialists have been skeptical of the usefulness of “advanced analytics” and “big data.” Often, the experience of working on several big data projects brings home the realization that these are crucial tools for navigating evolving and fluid financial crime and regulatory challenges.
How “big data” goes beyond basic analytics
The best-known approach to big data is through Hadoop, an open-source tool for exploiting advances in database management and search and discovery capabilities. Hadoop originated at Google and Yahoo and was designed to help make sense of the flood of data generated by the Internet.
Traditional database systems, including relational databases, organize only easy-to-categorize information, such as transactions, that typically exist in a particular data format. These days, though, professionals must be able to leverage growing amounts of unstructured data from social media, blogs, photo surveillance and other systems. Since data is stored in a variety of systems and devices, Hadoop and similar tools enable users to access and analyze data across different storage and source areas rapidly and efficiently.
With Hadoop and other tools, financial crime professionals can more easily, quickly and economically aggregate, analyze and manipulate huge quantities of data. They are no longer dependent on costly and time-consuming statistical and sampling methodologies that were required to assemble large amounts of data. No longer is it necessary to be selective about the types of data to be leveraged. In many cases, big data and analytics capabilities can even leverage and analyze data where it resides without the need to map or cleanse it.
Emerging analytical capabilities such as graph analytics can transform the compliance function of an institution or company by enhancing its ability to discover emerging threats or patterns that normal surveillance would miss. With these capabilities, compliance teams can augment traditional analytics and move from search-based to discovery-based analyses. This would allow them to react exponentially faster to changing financial crime threats.
Advanced analytics help detect sophisticated financial crime threats
The compliance units at financial institutions and other financial services organizations are grappling with an explosion of data related to the monitoring and reporting requirements of anti-money laundering laws and regulations of many countries, such as the Bank Secrecy Act in the United States. As firms respond to escalating and regulatory expectations that are starting to expand into other areas, such as compliance with foreign corruption and the Foreign Account Tax Compliance Act (FATCA), they seek better ways to identify new threats.
Emerging analytical capabilities offer compelling advantages to present practices. They complement existing technologies, enable business organizations to control cost escalation through greater efficiencies despite expanding data volumes, and power discovery of hidden or emerging financial crime patterns to ensure that nothing is missed.
Most importantly, these technologies may be integrated and overlaid with the solutions that the compliance teams business organizations are already using. There is no need to discard the technology, infrastructure and process investments that have already been made. Big data analytical approaches may be leveraged to make them better.
How Big Data may achieve better results:
- Customer risk assessment – onboarding and ongoing Know Your Customer (KYC): Achieve more consistent identification of a customer’s existing relationships and accounts across product types, lines of business and subsidiaries. Build a more complete risk assessment at the beginning through access to more complete data without increasing the cost or time required to access and pull data together.
- Smarter transaction monitoring and surveillance: Leverage analytics to further refine the output of the organization’s transaction monitoring software, reduce the number of false positive alerts, and generate more actionable alerts and exceptions.
- More efficient investigations: Streamline search and discovery of relevant information from internal and external sources, such as searches through third-party vendor data, unstructured web and social media, among other activities. Discover complex relationships, such as financial crime and money laundering rings, use data directly from source systems, and extend the ability to discover emerging and significant financial crime threats.
Note: Data analytics will be covered on a crucial panel at the ACFCS 2014 International Financial Crime Conference February 5-7, 2014 at the Marriott Marquis in New York City. For more information, click here.
*Karen Van Ness is Principal Consultant for Compliance Risk Solutions in Austin, Texas and a member of the ACFCS Advisory Board. She is an accomplished financial crime and compliance professional with over 20 years of experience in the compliance and risk, software and analytics, and financial services industries. She has played a key role in bringing to market monitoring and analytics solutions targeted to financial crime and compliance for leading firms such as Mantas, Oracle and LexisNexis Risk Solutions.